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<front>
<journal-meta>
<journal-id journal-id-type="issn">2767-0279</journal-id>
<journal-title-group>
<journal-title>Glossa Psycholinguistics</journal-title>
</journal-title-group>
<issn pub-type="epub">2767-0279</issn>
<publisher>
<publisher-name>eScholarship Publishing</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5070/G60111425</article-id>
<article-categories>
<subj-group>
<subject>Regular article</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>A Meta-analysis of syntactic satiation in extraction from islands</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Lu</surname>
<given-names>Jiayi</given-names>
</name>
<email>jiayi.lu@stanford.edu</email>
<xref ref-type="aff" rid="aff-1">1</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Frank</surname>
<given-names>Michael C.</given-names>
</name>
<email>mcfrank@stanford.edu</email>
<xref ref-type="aff" rid="aff-2">2</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Degen</surname>
<given-names>Judith</given-names>
</name>
<email>jdegen@stanford.edu</email>
<xref ref-type="aff" rid="aff-1">1</xref>
</contrib>
</contrib-group>
<aff id="aff-1"><label>1</label>Department of Linguistics, Stanford University, US</aff>
<aff id="aff-2"><label>2</label>Department of Psychology, Stanford University, US</aff>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2024-04-30">
<day>30</day>
<month>04</month>
<year>2024</year>
</pub-date>
<pub-date pub-type="collection">
<year>2024</year>
</pub-date>
<volume>3</volume>
<issue>1</issue>
<elocation-id>10</elocation-id>
<permissions>
<copyright-statement>Copyright: &#x00A9; 2024 The Author(s)</copyright-statement>
<copyright-year>2024</copyright-year>
<license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/4.0/">
<license-p>This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See <uri xlink:href="http://creativecommons.org/licenses/by/4.0/">http://creativecommons.org/licenses/by/4.0/</uri>.</license-p>
</license>
</permissions>
<self-uri xlink:href="https://glossapsycholinguistics.journalpub.escholarship.org/articles/10.5070/G60111425/"/>
<abstract>
<p>Sentence acceptability judgments are often affected by a pervasive phenomenon called <italic>satiation</italic>: native speakers give increasingly higher ratings to initially degraded sentences after repeated exposure. Various studies have investigated the satiation effect experimentally, the vast majority of which focused on different types of island-violating sentences in English (sentences with illicit long-distance syntactic movements). However, mixed findings are reported regarding which types of island violations are affected by satiation and which ones are not. This article presents a meta-analysis of past experimental studies on the satiation of island effects in English, with the aim of providing accurate estimates of the rate of satiation for each type of island, testing whether different island effects show different rates of satiation, exploring potential factors that contributed to the heterogeneity in past results, and spotting possible publication bias. The meta-analysis shows that adjunct islands, the Complex NP Constraint (CNPC), subject islands, the <italic>that</italic>-trace effect, the <italic>want-for</italic> construction, and <italic>whether</italic>-islands reliably exhibit satiation, albeit at different rates. No evidence for satiation is found for the Left Branch Condition (LBC). Whether context sentences were presented in the original acceptability judgment experiments predicts the differences in the rates of satiation reported across studies. Potential publication bias is found among studies testing the CNPC and <italic>whether</italic>-islands. These meta-analytic results can be used to inform debates regarding the nature of island effects and serve as a proof of concept that meta-analysis can be a valuable tool for linguistic research.</p>
</abstract>
</article-meta>
</front>
<body>
<sec>
<title>1. Introduction</title>
<p>Linguists have long relied on acceptability judgments by native speakers, collected either introspectively or experimentally, to inform syntactic theory (<xref ref-type="bibr" rid="B73">Schutze, 1996</xref>). Recent studies found that acceptability judgments are affected by a pervasive phenomenon called <italic>syntactic satiation</italic>, or simply <italic>satiation</italic>: participants in acceptability rating experiments rate degraded sentences as increasingly acceptable as they see more instances of such sentences (<xref ref-type="bibr" rid="B9">Braze, 2002</xref>; <xref ref-type="bibr" rid="B40">Hiramatsu, 2001</xref>; <xref ref-type="bibr" rid="B75">Snyder, 2000</xref>, <italic>inter alia</italic>). The satiation effect has recently drawn much attention, and there is an abundance of experimental studies testing whether various unacceptable sentence types satiate in English (<xref ref-type="bibr" rid="B9">Braze, 2002</xref>; <xref ref-type="bibr" rid="B15">Chaves &amp; Dery, 2014</xref>, <xref ref-type="bibr" rid="B16">2019</xref>; <xref ref-type="bibr" rid="B23">Crawford, 2012</xref>; <xref ref-type="bibr" rid="B25">Do &amp; Kaiser, 2017</xref>; <xref ref-type="bibr" rid="B31">Francom, 2009</xref>; <xref ref-type="bibr" rid="B35">Goodall, 2011</xref>; <xref ref-type="bibr" rid="B40">Hiramatsu, 2001</xref>; <xref ref-type="bibr" rid="B56">Lu et al., 2021</xref>, <xref ref-type="bibr" rid="B58">2022</xref>; <xref ref-type="bibr" rid="B75">Snyder, 2000</xref>, <xref ref-type="bibr" rid="B76">2022a</xref>; <xref ref-type="bibr" rid="B81">Sprouse, 2009</xref>) and other languages (<xref ref-type="bibr" rid="B2">Abugharsa, 2016</xref>; <xref ref-type="bibr" rid="B11">Brown et al., 2021</xref>; <xref ref-type="bibr" rid="B35">Goodall, 2011</xref>; <xref ref-type="bibr" rid="B61">Myers, 2012</xref>; <xref ref-type="bibr" rid="B78">Sommer, 2022</xref>). However, the satiation literature is replete with mixed empirical findings and non-replications regarding which sentence types are affected by satiation (see <xref ref-type="bibr" rid="B77">Snyder, 2022b</xref>, for a review), thus hindering the development of a coherent theoretical picture.</p>
<p>Quantitative meta-analysis offers the promise of remedying this situation. Meta-analysis is a statistical procedure for synthesizing information from multiple studies, thereby providing more precise estimates of an effect size than any single study (<xref ref-type="bibr" rid="B6">Borenstein et al., 2009</xref>). In addition, meta-analysis also allows the researcher to investigate the extent to which an effect varies across studies, and if so, to test whether certain study characteristics systematically produce different results. Meta-analysis is a commonly employed method in a wide variety of fields, including medicine (<xref ref-type="bibr" rid="B38">Haidich, 2010</xref>; <xref ref-type="bibr" rid="B54">L&#8217;Abb&#233; et al., 1987</xref>), education (<xref ref-type="bibr" rid="B33">Glass, 1976</xref>; <xref ref-type="bibr" rid="B74">Slavin, 1984</xref>), criminology (<xref ref-type="bibr" rid="B66">Pratt, 2010</xref>; <xref ref-type="bibr" rid="B87">Turanovic &amp; Pratt, 2021</xref>), business (<xref ref-type="bibr" rid="B48">Kirca &amp; Yaprak, 2010</xref>), ecology (<xref ref-type="bibr" rid="B36">Gurevitch et al., 2001</xref>), and even other areas of psycholinguistics (<xref ref-type="bibr" rid="B4">Bergmann et al., 2018</xref>; <xref ref-type="bibr" rid="B12">Cao &amp; Lewis, 2022</xref>; <xref ref-type="bibr" rid="B13">Cao et al., 2023</xref>).</p>
<p>In the current study, we present a meta-analysis of past findings in the satiation literature, with the aim of assessing which sentence types reliably satiate. Specifically, we limit our focus to past studies examining the satiation of <italic>island effects</italic>: the degradation in acceptability of sentences that include long-distance syntactic movement operations that are illicit according to standard syntactic theories (<xref ref-type="bibr" rid="B69">Ross, 1967</xref>). There are two reasons to restrict the domain of study to island effects. First, the vast majority of past experimental studies on satiation has exclusively tested sentences with island violations, making island effects the only syntactic domain where a meta-analysis has sufficient statistical power and thus the potential to be informative. Second, findings from the literature on satiation have been used to adjudicate between different theories in the domain of island effects. Therefore, the results of a meta-analysis on the satiation of island effects could help inform theoretical claims in the island literature.</p>
<p>In the remainder of this section, we introduce island effects and the satiation effect, respectively. We then provide statistical background on meta-analysis and report a meta-analysis we conducted on 25 island satiation experiments in Section 2. Finally, we discuss the implications of these results in Section 3, focusing especially on their potential for adjudicating between grammatical and processing accounts of island effects.</p>
<sec>
<title>1.1 Island effects</title>
<p>There is a long-standing generalization that certain structural domains restrict syntactic movement operations, a phenomenon termed <italic>island effects</italic> (<xref ref-type="bibr" rid="B69">Ross, 1967</xref>). Attempting to extract from islands results in degraded sentence acceptability, as in the examples in (1), all involving illicit wh-movement.<xref ref-type="fn" rid="n1">1</xref></p>
<list list-type="gloss">
<list-item>
<list list-type="wordfirst">
<list-item><p>(1)</p></list-item>
</list>
</list-item>
<list-item>
<list list-type="sentence-gloss">
<list-item>
<list list-type="final-sentence">
<list-item><p>&#160;&#160;Island-violating sentences&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;(<xref ref-type="bibr" rid="B75">Snyder, 2000, p. 576</xref>)</p></list-item>
</list>
</list-item>
</list>
</list-item>
</list>
<list list-type="gloss">
<list-item>
<list list-type="wordfirst">
<list-item><p>&#160;</p></list-item>
</list>
<list list-type="wordfirst">
<list-item><p>a.</p></list-item>
</list>
</list-item>
<list-item>
<list list-type="sentence-gloss">
<list-item>
<list list-type="final-sentence">
<list-item><p>&#160;&#160;The Left Branch Condition</p></list-item>
<list-item><p>*How many<italic><sub>i</sub></italic> did John buy <italic>t<sub>i</sub></italic> books?</p></list-item>
</list>
</list-item>
</list>
</list-item>
</list>
<list list-type="gloss">
<list-item>
<list list-type="wordfirst">
<list-item><p>&#160;</p></list-item>
</list>
<list list-type="wordfirst">
<list-item><p>b.</p></list-item>
</list>
</list-item>
<list-item>
<list list-type="sentence-gloss">
<list-item>
<list list-type="final-sentence">
<list-item><p>&#160;&#160;Adjunct island</p></list-item>
<list-item><p>*Who<italic><sub>i</sub></italic> did John talk with Mary after seeing <italic>t<sub>i</sub></italic>?</p></list-item>
</list>
</list-item>
</list>
</list-item>
</list>
<list list-type="gloss">
<list-item>
<list list-type="wordfirst">
<list-item><p>&#160;</p></list-item>
</list>
<list list-type="wordfirst">
<list-item><p>c.</p></list-item>
</list>
</list-item>
<list-item>
<list list-type="sentence-gloss">
<list-item>
<list list-type="final-sentence">
<list-item><p>&#160;&#160;The Complex NP Constraint (CNPC)</p></list-item>
<list-item><p>*Who<italic><sub>i</sub></italic> does Mary believe the claim that John likes <italic>t<sub>i</sub></italic>?</p></list-item>
</list>
</list-item>
</list>
</list-item>
</list>
<list list-type="gloss">
<list-item>
<list list-type="wordfirst">
<list-item><p>&#160;</p></list-item>
</list>
<list list-type="wordfirst">
<list-item><p>d.</p></list-item>
</list>
</list-item>
<list-item>
<list list-type="sentence-gloss">
<list-item>
<list list-type="final-sentence">
<list-item><p>&#160;&#160;Subject island</p></list-item>
<list-item><p>*What<italic><sub>i</sub></italic> does John know that a bottle of <italic>t<sub>i</sub></italic> fell on the floor?</p></list-item>
</list>
</list-item>
</list>
</list-item>
</list>
<list list-type="gloss">
<list-item>
<list list-type="wordfirst">
<list-item><p>&#160;</p></list-item>
</list>
<list list-type="wordfirst">
<list-item><p>e.</p></list-item>
</list>
</list-item>
<list-item>
<list list-type="sentence-gloss">
<list-item>
<list list-type="final-sentence">
<list-item><p>&#160;&#160;The <italic>that</italic>-trace effect</p></list-item>
<list-item><p>*Who<italic><sub>i</sub></italic> does Mary think that <italic>t<sub>i</sub></italic> likes John?</p></list-item>
</list>
</list-item>
</list>
</list-item>
</list>
<list list-type="gloss">
<list-item>
<list list-type="wordfirst">
<list-item><p>&#160;</p></list-item>
</list>
<list list-type="wordfirst">
<list-item><p>f.</p></list-item>
</list>
</list-item>
<list-item>
<list list-type="sentence-gloss">
<list-item>
<list list-type="final-sentence">
<list-item><p>&#160;&#160;The <italic>want-for</italic> construction</p></list-item>
<list-item><p>*Who<italic><sub>i</sub></italic> does John want for Mary to meet <italic>t<sub>i</sub></italic>?</p></list-item>
</list>
</list-item>
</list>
</list-item>
</list>
<list list-type="gloss">
<list-item>
<list list-type="wordfirst">
<list-item><p>&#160;</p></list-item>
</list>
<list list-type="wordfirst">
<list-item><p>g.</p></list-item>
</list>
</list-item>
<list-item>
<list list-type="sentence-gloss">
<list-item>
<list list-type="final-sentence">
<list-item><p>&#160;&#160;<italic>Whether</italic>-island</p></list-item>
<list-item><p>*Who<italic><sub>i</sub></italic> does John wonder whether Mary likes <italic>t<sub>i</sub></italic>?</p></list-item>
</list>
</list-item>
</list>
</list-item>
</list>
<p>The nature of these island effects has been a long-standing source of debate in the linguistic literature. The degraded acceptability of island-violating sentences like (1a-g) has been variably attributed to constraints in <italic>grammar</italic> (<xref ref-type="bibr" rid="B10">Bresnan, 1976</xref>; <xref ref-type="bibr" rid="B18">Chomsky, 1964</xref>, <xref ref-type="bibr" rid="B19">1973</xref>, <xref ref-type="bibr" rid="B20">1977</xref>, <xref ref-type="bibr" rid="B21">1986</xref>; <xref ref-type="bibr" rid="B44">Huang, 1982</xref>; <xref ref-type="bibr" rid="B67">Rizzi, 1990</xref>; <xref ref-type="bibr" rid="B69">Ross, 1967</xref>; <xref ref-type="bibr" rid="B71">Sag, 1976</xref>) or <italic>processing</italic> (<xref ref-type="bibr" rid="B24">Culicover et al., 2022</xref>; <xref ref-type="bibr" rid="B41">Hofmeister et al., 2013</xref>; <xref ref-type="bibr" rid="B43">Hofmeister &amp; Sag, 2010</xref>; <xref ref-type="bibr" rid="B49">Kluender, 1991</xref>; <xref ref-type="bibr" rid="B50">Kluender &amp; Kutas, 1993</xref>).<xref ref-type="fn" rid="n2">2</xref> Grammar-based approaches to island effects claim that the sentences in (1) are ungrammatical because they violate certain grammatical constraints (e.g., the Subjacency Condition, the Phase Impenetrability Condition, etc.). Processing-based approaches to island effects claim that the sentences in (1) are grammatical, but are unacceptable due to the high processing burdens they incur (analogous to the difficulty in processing center-embedding sentences).</p>
<p>In addition to the debate over whether island effects are best explained as the result of grammatical or processing factors, there is a lack of consensus regarding whether certain islands form natural classes. For example, some have grouped subject and adjunct islands together as a natural class in opposition to the other island types, and have attributed the two distinct classes of islands to two different constraints in the grammar (<xref ref-type="bibr" rid="B21">Chomsky, 1986</xref>; <xref ref-type="bibr" rid="B44">Huang, 1982</xref>; <xref ref-type="bibr" rid="B62">Nunes &amp; Uriagereka, 2000</xref>). Others, however, reject this grouping, either proposing that subject and adjunct island effects involve different grammatical constraints (<xref ref-type="bibr" rid="B37">Haegeman et al., 2014</xref>; <xref ref-type="bibr" rid="B40">Hiramatsu, 2001</xref>; <xref ref-type="bibr" rid="B84">Stepanov, 2007</xref>), or arguing for a unifying (syntactic, information structural, or processing-based) account of a larger set of island effects, including but not limited to subject and adjunct island effects (<xref ref-type="bibr" rid="B1">Abeill&#233; et al., 2020</xref>; <xref ref-type="bibr" rid="B8">Bo&#353;kovi&#263;, 2016</xref>; <xref ref-type="bibr" rid="B27">Erteschik-Shir, 1973</xref>; <xref ref-type="bibr" rid="B34">Goldberg, 2013</xref>). In sum, the island literature lacks a consensus on the source and nature of island effects.</p>
</sec>
<sec>
<title>1.2 Satiation</title>
<p>The effect of repeated exposure on the perceived acceptability of island-violating sentences has been brought to bear on the debate over grammatical vs. processing accounts of island effects. A linking assumption that has been (implicitly or explicitly) adopted by some. is that degraded acceptability due to grammatical violations should not be affected by repeated exposure. In contrast, if the source of degraded acceptability is processing difficulty, exposing participants to similar sentences of the same type should increase familiarity with this sentence type and ease the associated processing burden. In turn, acceptability should increase with repeated exposure (i.e., show the satiation effect).<xref ref-type="fn" rid="n3">3</xref> If we accept this linking hypothesis, whether or not the acceptability of island-violating sentences increases with exposure can been used to diagnose whether certain island effects are grammatical or the result of processing constraints.</p>
<p>Acceptability increase after exposure, or the <italic>satiation effect</italic> (<xref ref-type="bibr" rid="B86">Stromswold, 1986</xref>), was first demonstrated experimentally for island-violating sentences in Snyder (<xref ref-type="bibr" rid="B75">2000</xref>).<xref ref-type="fn" rid="n4">4</xref> The observation of satiation effects in island-violating sentences has subsequently been interpreted as evidence for the extra-grammatical nature of islands, including the Complex NP Constraint (<xref ref-type="bibr" rid="B43">Hofmeister &amp; Sag, 2010</xref>), the superiority effect (<xref ref-type="bibr" rid="B42">Hofmeister et al., 2011</xref>), and subject islands (<xref ref-type="bibr" rid="B14">Chaves, 2022</xref>; <xref ref-type="bibr" rid="B15">Chaves &amp; Dery, 2014</xref>, <xref ref-type="bibr" rid="B16">2019</xref>).</p>
<p>Other studies assume a different linking hypothesis for the satiation effect, whereby certain grammatical constraints may also be &#8220;unlearned&#8221; or weakened throughout repeated exposure to sentences violating those constraints, and differences in satiation profiles reflect differences in the types of grammatical constraints involved (<xref ref-type="bibr" rid="B9">Braze, 2002</xref>; <xref ref-type="bibr" rid="B35">Goodall, 2011</xref>; <xref ref-type="bibr" rid="B40">Hiramatsu, 2001</xref>; <xref ref-type="bibr" rid="B75">Snyder, 2000</xref>). Assuming this hypothesis, satiation results cannot be used to inform the grammar vs. processing debate regarding the nature of islands. Instead, satiation can be used to probe for natural classes formed by different islands. If two island types show different patterns of satiation (e.g., one satiates, while the other does not), they are assumed to have different underlying sources of unacceptability and should not be grouped together as a natural class. This linking hypothesis underlies the argument against Huang&#8217;s (<xref ref-type="bibr" rid="B44">1982</xref>) proposal that subject and adjunct islands form a natural class (<xref ref-type="bibr" rid="B40">Hiramatsu, 2001</xref>; <xref ref-type="bibr" rid="B84">Stepanov, 2007</xref>).</p>
<p>In sum, while assuming slightly different linking hypotheses, the satiation effect has been used as evidence in multiple debates surrounding the nature of island effects.<xref ref-type="fn" rid="n5">5</xref> In the current study, our goal is not to further complicate the picture by taking sides in any of these debates. We also remain agnostic about which linking hypothesis for satiation is appropriate. Instead, we aim to clarify the empirical landscape on satiation so that satiation can be better leveraged as a source of evidence.</p>
<p>As mentioned earlier, the satiation literature abounds with mixed findings. Statistically significant satiation of island effects has been observed with some experimental procedures and items, but these effects have been inconsistent (see <xref ref-type="bibr" rid="B77">Snyder, 2022b</xref>, for a comprehensive overview). For example, the adjunct island is found to satiate in Chaves &amp; Putnam (<xref ref-type="bibr" rid="B17">2020</xref>), but not in Crawford (<xref ref-type="bibr" rid="B23">2012</xref>); Francom (<xref ref-type="bibr" rid="B31">2009</xref>); Hiramatsu (<xref ref-type="bibr" rid="B40">2001</xref>); Snyder (<xref ref-type="bibr" rid="B75">2000</xref>); Sprouse (<xref ref-type="bibr" rid="B81">2009</xref>, <italic>inter alia</italic>). For a comprehensive list of past satiation studies and whether they observed satiation in each island type, the reader is referred to <xref ref-type="table" rid="T4">Tables 4</xref> and 5 from Snyder (<xref ref-type="bibr" rid="B76">2022a</xref>). The current study reports a quantitative meta-analysis of past satiation studies, with the aim of summarizing and aggregating past findings in the service of assessing which island types reliably satiate.</p>
</sec>
</sec>
<sec>
<title>2. A meta-analysis of island effect satiation</title>
<p>Meta-analysis is a way to systematically synthesize evidence from multiple studies to estimate effect size more precisely than is possible in an individual study, and discover inconsistencies between studies (<xref ref-type="bibr" rid="B6">Borenstein et al., 2009</xref>). This practice is particularly important in a field like linguistics, where many experimental studies are plagued by low statistical power, leading to mixed results and non-replications (<xref ref-type="bibr" rid="B88">Vasishth &amp; Gelman, 2021</xref>; <xref ref-type="bibr" rid="B89">Vasishth et al., 2018</xref>).</p>
<p>The main goal of a meta-analysis is to give an effect size estimate informed by the effect size estimates from multiple studies. In particular, the effect size estimate is taken to be the average of all effect sizes weighted by how reliable or informative they are, based on their variance. Different statistical models can be used to achieve this goal, which makes different assumptions about the homogeneity of the effect: fixed-effects or random-effects meta-analytic models.<xref ref-type="fn" rid="n6">6</xref></p>
<p>The fixed-effects model provides an estimate of the effect size <inline-formula>
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</inline-formula> weighted by the inverse of the variance of the data, as shown in (E1). This weighted average approach is intuitively justified: larger and more informative studies with less variance should be given more weight in the model compared to smaller studies with greater variance.</p>
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<p>In many cases, the estimated effect may vary across the studies included in a meta-analysis due to differences in experimental methods or the sampling process. The fixed-effects meta-analytic model, which assumes a single population effect size for all studies, does not take such heterogeneity into account. In contrast, a random-effects meta-analytic model assumes the population effects of all studies come from a normal distribution with mean &#956; and standard deviation <italic>&#964;</italic>, as shown in (E2).</p>
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<p>The model then provides estimates for <italic>&#964;</italic> in addition to the effect estimate &#956;. As shown in (E3), the random-effects meta-analytic model estimates the effect size as an average of each study&#8217;s point estimate, weighted by the inverse of each study&#8217;s variance adjusted by the estimated between-study variance <inline-formula>
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<p>Since there is variation in methods and designs across satiation studies, we use the random-effects model instead of the fixed-effects model for our meta-analysis.</p>
<p>The random-effects meta-analytic model does not provide a structured analysis of the factors that contribute to the cross-study heterogeneity. To investigate heterogeneity, one can include different moderators (study-level factors that may affect effect size) to form a mixed-effects meta-analytic model as in (E4), where <italic>x<sub>ij</sub></italic> represents the <italic>j<sup>th</sup></italic> moderator for the <italic>i<sup>th</sup></italic> study. From the parameter estimates <italic>&#946;</italic><sub>1</sub> to <italic>&#946;<sub>j</sub></italic>, we can infer whether the moderators influence the effect size.</p>
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<p>Finally, meta-analyses can also be used to detect publication bias, the tendency for studies reporting null results to not get published. One simple way to do so is by creating a <italic>funnel plot</italic>: a scatter plot of effect size against standard error (<xref ref-type="bibr" rid="B55">Light &amp; Pillemer, 1984</xref>).<xref ref-type="fn" rid="n7">7</xref> In absence of heterogeneity or publication bias, studies with smaller standard errors are expected to have effect sizes closer to the meta-analytic estimate, and those with larger standard errors to spread out further. Thus, the scatter plot should show a funnel shape (hence the name <italic>funnel plot</italic>), as shown in the hypothetical plot in <xref ref-type="fig" rid="F1">Figure 1a</xref>. The white funnel-shaped area in the plot represents the 95% confidence interval for the observed effects calculated based on the meta-analytic estimate and the standard error, and serves as a visual aid for what the funnel-shaped distribution should look like in the absence of any publication bias. In contrast, if there is publication bias, studies with positive effect estimates are more likely to be reported. As a result, the funnel plot should show an asymmetric distribution in the shape of a right-skewed triangle rather than a funnel. An example is shown in <xref ref-type="fig" rid="F1">Figure 1b</xref>. The existence of a publication bias can be statistically confirmed using Egger&#8217;s regression test on funnel plot asymmetry (<xref ref-type="bibr" rid="B26">Egger et al., 1997</xref>), which detects a correlation between the effect size and standard error. A significant correlation suggests that the funnel plot is asymmetric and that there is potentially a publication bias.</p>
<fig id="F1">
<caption>
<p><bold>Figure 1:</bold> Hypothetical funnel plots showing standard error against effect estimate for each individual study. The dashed vertical line indicates the meta-analytic effect size estimate.</p>
</caption>
<graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="glossapx-3-1-1425-g1.png"/>
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<p>In the study reported below, we conducted a meta-analysis of satiation in seven different island types. We report analyses of satiation effect estimates, heterogeneity, and publication bias for each island type.</p>
<sec sec-type="methods">
<title>2.1 Method</title>
<sec>
<title>2.1.1 Dataset selection</title>
<p>The study selection process is summarized in <xref ref-type="fig" rid="F2">Figure 2</xref>, which depicts a PRISMA flow chart (<xref ref-type="bibr" rid="B60">Moher et al., 2009</xref>). Our goal was to include as many studies as possible on island satiation effects in English. To this end, we first collected all results returned on the first 20 pages of Google Scholar with the search keywords &#8220;syntactic satiation&#8221; (200 entries). Excluding 3 duplicate entries, 3 non-English entries, and 20 entries without links to full text or abstract, we then screened the abstracts of the remaining 174 entries and excluded 150 entries that did not report any experimental study on satiation. This narrowed the selection down to 24 entries. After accessing the full text of these 24 entries, we excluded 5 entries that did not study the satiation of island effects in English, and 3 entries whose experimental results were also reported in other publications by the same authors.</p>
<fig id="F2">
<caption>
<p><bold>Figure 2:</bold> PRISMA flow chart summarizing the study selection process.</p>
</caption>
<graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="glossapx-3-1-1425-g2.png"/>
</fig>
<p>Since not all studies used the same method of data processing and statistical analysis, we reached out to all authors for the raw data files, so that we could extract effect size estimates from the data in a systematic and comparable manner. Our final analysis included all selected papers whose raw data files were kindly made available by the authors, in addition to those that directly reported the measurements we planned to use in the meta-analysis (unit satiation per repetition), which we introduce in detail in the next section. Five papers were excluded from the meta-analysis, because the relevant effect sizes were not reported and could not be computed from the reported statistics, and the data files were not made available.</p>
<p>For the purpose of standardizing effect estimates across different studies, we only summarized experiments that employed acceptability judgment experiments with closed rating scales.<xref ref-type="fn" rid="n8">8</xref> Although this meta-analysis was not pre-registered, all inclusion criteria are determined before computing meta-analytic estimates. The following studies were included based on our selection criteria: Snyder (<xref ref-type="bibr" rid="B75">2000</xref>), Experiments 1 and 2 of Francom (<xref ref-type="bibr" rid="B31">2009</xref>), the three replication experiments reported in Section 2 of Sprouse (<xref ref-type="bibr" rid="B81">2009</xref>) (labeled Exp.1a, b, c, respectively, in the discussion below), and the two experiments reported in Section 4 of the same paper (labeled Exp.2a and b below), Experiments 1 and 2 of Francom (<xref ref-type="bibr" rid="B31">2009</xref>), Hofmeister &amp; Sag (<xref ref-type="bibr" rid="B43">2010</xref>), Crawford (<xref ref-type="bibr" rid="B23">2012</xref>), Experiments 1 and 2 of Chaves &amp; Dery (<xref ref-type="bibr" rid="B15">2014</xref>), Experiment 1 of Do &amp; Kaiser (<xref ref-type="bibr" rid="B25">2017</xref>) (the two sub-experiments &#8220;lag 1&#8221; and &#8220;lag 5&#8221; in the original paper are labeled as Exp.1a and Exp.1b, respectively, in the discussion below for simplicity), Chaves &amp; Dery (<xref ref-type="bibr" rid="B16">2019</xref>), the experiments reported in 6.2.2 (labeled Exp.1 below), 6.2.4 (the two sub-experiments labeled Exp.2a and 2b below), and 6.2.5 of Chaves &amp; Putnam (<xref ref-type="bibr" rid="B17">2020</xref>) (labeled Exp.3 below), Experiments 1 and 2 of Lu et al. (<xref ref-type="bibr" rid="B56">2021</xref>), Experiments 1 and 2 of Lu et al. (<xref ref-type="bibr" rid="B58">2022</xref>), and Experiments 1 and 3 of Snyder (<xref ref-type="bibr" rid="B76">2022a</xref>).<xref ref-type="fn" rid="n9">9</xref> See <xref ref-type="table" rid="T1">Table 1</xref> for a summary of the studies included and their reported findings. Please note that the studies in <xref ref-type="table" rid="T1">Table 1</xref> have vastly different sample sizes, and used different data processing and hypothesis testing methods to reach their conclusions on which island effects satiate. Therefore, any &#8220;vote-counting&#8221; procedure by comparing the numbers of studies finding significant satiation effects for each island type would not be informative.</p>
<table-wrap id="T1">
<caption>
<p><bold>Table 1:</bold> Summary of all studies included in the meta-analysis. For some studies, experiment numbering is added for ease of presentation (see section 2.1.1 for details). Each acronym refers to a type of island effect tested. AI: adjunct island; CNPC: Complex NP Constraint; CSC: coordinate structure constraint; LBC: left branch condition; RC: relative clause island; SI: subject island; TT: <italic>that</italic>-trace effect; WF: <italic>want-for</italic> construction; WI: <italic>whether</italic>-island.</p>
</caption>
<table>
<thead>
<tr>
<td align="left" valign="top"><bold>Study</bold></td>
<td align="left" valign="top"><bold>Sample size</bold></td>
<td align="left" valign="top"><bold>Reported satiating island(s)</bold></td>
<td align="left" valign="top"><bold>Reported non-satiating island(s)</bold></td>
<td align="left" valign="top"><bold>Repetition</bold></td>
<td align="left" valign="top"><bold>Scale</bold></td>
<td align="left" valign="top"><bold>Context</bold></td>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top">Snyder (<xref ref-type="bibr" rid="B75">2000</xref>)</td>
<td align="left" valign="top">22</td>
<td align="left" valign="top">CNPC, SI*, WI</td>
<td align="left" valign="top">AI, LBC, TT, WF</td>
<td align="left" valign="top">5</td>
<td align="left" valign="top">Binary</td>
<td align="left" valign="top">Yes</td>
</tr>
<tr>
<td align="left" valign="top">Francom (<xref ref-type="bibr" rid="B31">2009</xref>) Exp.1</td>
<td align="left" valign="top">205</td>
<td align="left" valign="top">SI, WF, WI</td>
<td align="left" valign="top">AI, CNPC, LBC, TT</td>
<td align="left" valign="top">5</td>
<td align="left" valign="top">Binary</td>
<td align="left" valign="top">No</td>
</tr>
<tr>
<td align="left" valign="top">Francom (<xref ref-type="bibr" rid="B31">2009</xref>) Exp.2</td>
<td align="left" valign="top">17</td>
<td align="left" valign="top">SI</td>
<td align="left" valign="top">CNPC, AI, TT, LBC</td>
<td align="left" valign="top">8</td>
<td align="left" valign="top">Binary</td>
<td align="left" valign="top">No</td>
</tr>
<tr>
<td align="left" valign="top">Sprouse (<xref ref-type="bibr" rid="B81">2009</xref>) Exp.1a</td>
<td align="left" valign="top">21</td>
<td align="left" valign="top"></td>
<td align="left" valign="top">AI, CNPC, LBC, SI, TT, WF, WI</td>
<td align="left" valign="top">5</td>
<td align="left" valign="top">Binary</td>
<td align="left" valign="top">No</td>
</tr>
<tr>
<td align="left" valign="top">Sprouse (<xref ref-type="bibr" rid="B81">2009</xref>) Exp.1b</td>
<td align="left" valign="top">21</td>
<td align="left" valign="top"></td>
<td align="left" valign="top">AI, CNPC, LBC, SI, TT, WF, WI</td>
<td align="left" valign="top">5</td>
<td align="left" valign="top">Binary</td>
<td align="left" valign="top">No</td>
</tr>
<tr>
<td align="left" valign="top">Sprouse (<xref ref-type="bibr" rid="B81">2009</xref>) Exp.1c</td>
<td align="left" valign="top">22</td>
<td align="left" valign="top"></td>
<td align="left" valign="top">AI, CNPC, LBC, SI, WI</td>
<td align="left" valign="top">5</td>
<td align="left" valign="top">Binary</td>
<td align="left" valign="top">No</td>
</tr>
<tr>
<td align="left" valign="top">Sprouse (<xref ref-type="bibr" rid="B81">2009</xref>) Exp.2a</td>
<td align="left" valign="top">25</td>
<td align="left" valign="top"></td>
<td align="left" valign="top">AI, CNPC, CSC, LBC, RC, SI, WI</td>
<td align="left" valign="top">10</td>
<td align="left" valign="top">Binary</td>
<td align="left" valign="top">No</td>
</tr>
<tr>
<td align="left" valign="top">Sprouse (<xref ref-type="bibr" rid="B81">2009</xref>) Exp.2b</td>
<td align="left" valign="top">25</td>
<td align="left" valign="top"></td>
<td align="left" valign="top">AI, CNPC, RC, WI</td>
<td align="left" valign="top">10</td>
<td align="left" valign="top">Binary</td>
<td align="left" valign="top">No</td>
</tr>
<tr>
<td align="left" valign="top">Hofmeister and Sag (<xref ref-type="bibr" rid="B43">2010</xref>)</td>
<td align="left" valign="top">22</td>
<td align="left" valign="top">CNPC</td>
<td align="left" valign="top"></td>
<td align="left" valign="top">31</td>
<td align="left" valign="top">Multi-point</td>
<td align="left" valign="top">No</td>
</tr>
<tr>
<td align="left" valign="top">Crawford (<xref ref-type="bibr" rid="B23">2012</xref>)</td>
<td align="left" valign="top">22</td>
<td align="left" valign="top">WI</td>
<td align="left" valign="top">AI, SI</td>
<td align="left" valign="top">7</td>
<td align="left" valign="top">Multi-point</td>
<td align="left" valign="top">Yes</td>
</tr>
<tr>
<td align="left" valign="top">Chaves and Dery (<xref ref-type="bibr" rid="B15">2014</xref>) Exp.1</td>
<td align="left" valign="top">60</td>
<td align="left" valign="top">SI</td>
<td align="left" valign="top"></td>
<td align="left" valign="top">20</td>
<td align="left" valign="top">Multi-point</td>
<td align="left" valign="top">No</td>
</tr>
<tr>
<td align="left" valign="top">Chaves and Dery (<xref ref-type="bibr" rid="B15">2014</xref>) Exp.2</td>
<td align="left" valign="top">51</td>
<td align="left" valign="top">SI</td>
<td align="left" valign="top"></td>
<td align="left" valign="top">14</td>
<td align="left" valign="top">Multi-point</td>
<td align="left" valign="top">No</td>
</tr>
<tr>
<td align="left" valign="top">Do and Kaiser (<xref ref-type="bibr" rid="B25">2017</xref>) Exp.1a</td>
<td align="left" valign="top">44</td>
<td align="left" valign="top">CNPC</td>
<td align="left" valign="top">SI</td>
<td align="left" valign="top">6</td>
<td align="left" valign="top">Multi-point</td>
<td align="left" valign="top">No</td>
</tr>
<tr>
<td align="left" valign="top">Do and Kaiser (<xref ref-type="bibr" rid="B25">2017</xref>) Exp.1b</td>
<td align="left" valign="top">40</td>
<td align="left" valign="top"></td>
<td align="left" valign="top">CNPC, SI</td>
<td align="left" valign="top">6</td>
<td align="left" valign="top">Multi-point</td>
<td align="left" valign="top">No</td>
</tr>
<tr>
<td align="left" valign="top">Chaves and Dery (<xref ref-type="bibr" rid="B16">2019</xref>)</td>
<td align="left" valign="top">48</td>
<td align="left" valign="top">SI</td>
<td align="left" valign="top"></td>
<td align="left" valign="top">22</td>
<td align="left" valign="top">Multi-point</td>
<td align="left" valign="top">No</td>
</tr>
<tr>
<td align="left" valign="top">Chaves and Putnam (<xref ref-type="bibr" rid="B17">2020</xref>) Exp.1</td>
<td align="left" valign="top">74</td>
<td align="left" valign="top">SI</td>
<td align="left" valign="top"></td>
<td align="left" valign="top">16</td>
<td align="left" valign="top">Multi-point</td>
<td align="left" valign="top">No</td>
</tr>
<tr>
<td align="left" valign="top">Chaves and Putnam (<xref ref-type="bibr" rid="B17">2020</xref>) Exp.2a</td>
<td align="left" valign="top">40</td>
<td align="left" valign="top">AI</td>
<td align="left" valign="top"></td>
<td align="left" valign="top">12</td>
<td align="left" valign="top">Multi-point</td>
<td align="left" valign="top">No</td>
</tr>
<tr>
<td align="left" valign="top">Chaves and Putnam (<xref ref-type="bibr" rid="B17">2020</xref>) Exp.2b</td>
<td align="left" valign="top">40</td>
<td align="left" valign="top">AI</td>
<td align="left" valign="top"></td>
<td align="left" valign="top">6</td>
<td align="left" valign="top">Multi-point</td>
<td align="left" valign="top">No</td>
</tr>
<tr>
<td align="left" valign="top">Chaves and Putnam (<xref ref-type="bibr" rid="B17">2020</xref>) Exp.3</td>
<td align="left" valign="top">106</td>
<td align="left" valign="top">AI</td>
<td align="left" valign="top"></td>
<td align="left" valign="top">24</td>
<td align="left" valign="top">Multi-point</td>
<td align="left" valign="top">No</td>
</tr>
<tr>
<td align="left" valign="top">Lu, Lassiter, and Degen (<xref ref-type="bibr" rid="B56">2021</xref>) Exp.1</td>
<td align="left" valign="top">106</td>
<td align="left" valign="top">CNPC, SI, WI</td>
<td align="left" valign="top"></td>
<td align="left" valign="top">15</td>
<td align="left" valign="top">Multi-point</td>
<td align="left" valign="top">Yes</td>
</tr>
<tr>
<td align="left" valign="top">Lu, Lassiter, and Degen (<xref ref-type="bibr" rid="B56">2021</xref>) Exp.2</td>
<td align="left" valign="top">102</td>
<td align="left" valign="top">CNPC, SI, WI</td>
<td align="left" valign="top"></td>
<td align="left" valign="top">15</td>
<td align="left" valign="top">Multi-point</td>
<td align="left" valign="top">Yes</td>
</tr>
<tr>
<td align="left" valign="top">Lu, Wright, and Degen (<xref ref-type="bibr" rid="B58">2022</xref>) Exp.1</td>
<td align="left" valign="top">294</td>
<td align="left" valign="top">SI, WI</td>
<td align="left" valign="top"></td>
<td align="left" valign="top">12</td>
<td align="left" valign="top">Multi-point</td>
<td align="left" valign="top">Yes</td>
</tr>
<tr>
<td align="left" valign="top">Lu, Wright, and Degen (<xref ref-type="bibr" rid="B58">2022</xref>) Exp.2</td>
<td align="left" valign="top">311</td>
<td align="left" valign="top">SI, WI</td>
<td align="left" valign="top"></td>
<td align="left" valign="top">12</td>
<td align="left" valign="top">Multi-point</td>
<td align="left" valign="top">Yes</td>
</tr>
<tr>
<td align="left" valign="top">Snyder (2022) Exp.1</td>
<td align="left" valign="top">20</td>
<td align="left" valign="top">WI</td>
<td align="left" valign="top">CNPC, LBC, SI</td>
<td align="left" valign="top">5</td>
<td align="left" valign="top">Binary</td>
<td align="left" valign="top">Yes</td>
</tr>
<tr>
<td align="left" valign="top">Snyder (2022) Exp.3</td>
<td align="left" valign="top">151</td>
<td align="left" valign="top">CNPC, WI</td>
<td align="left" valign="top">AI, LBC, SI, TT, WF</td>
<td align="left" valign="top">5</td>
<td align="left" valign="top">Binary</td>
<td align="left" valign="top">Yes</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>*: Only marginal significance reported.</p>
</table-wrap-foot>
</table-wrap>
</sec>
<sec>
<title>2.1.2 Meta-analytic methods</title>
<p>We first grouped the selected studies by the island types they investigated. When a paper contained multiple experiments, each experiment was treated as a different study. When a study tested multiple variants of the same island effect type (e.g., the subject island effect induced by extraction from DP subjects vs. CP subjects), the different variants were treated as the same island type for the purpose of our analysis. A total of seven island types (those shown in (1)), each studied in at least three experiments, were included in the meta-analysis.</p>
<p>We defined satiation as a positive main effect of the number of repetitions of an island-violating sentence type on the acceptability of that sentence type. We chose the number of repetitions, instead of the overall experimental trial number, as the predictor, because different studies included different numbers of fillers, and not all raw data files provided by the authors contained filler information. We detected satiation as a main effect of repetition number of island-violating sentences, rather than as the change in contrast between island-violating sentences and a non-satiating grammatical control, because various studies included in the meta-analysis either did not include a grammatical control condition or included non-satiating control conditions in their design, but did not include the results for the control sentences in the data files made available. For consistency, we only analyzed the change in absolute acceptability ratings of the island-violating sentence types.<xref ref-type="fn" rid="n10">10</xref></p>
<p>Many meta-analyses are conducted across standardized unitless effect size measures (e.g., Cohen&#8217;s d) to ensure comparability of effects across studies. However, we are interested in a particular effect size that has interpretable units: change in acceptability (0&#8211;1) per sentence repetition. If we computed standardized effects as is typical, we would run the risk of combining effects from studies with different definitions for satiation, using different satiation manipulations, and measuring acceptability with different scales. In contrast, our acceptability per repetition effect is much more interpretable in its magnitude across studies than a standardized effect. Therefore, we depart from standard meta-analyses, and compute effect sizes and measures of variation directly from raw data files of the original studies, either available in the public domain or provided by the authors upon request.<xref ref-type="fn" rid="n11">11</xref></p>
<p>To compute the quantity needed for meta-analysis, we first linearly transformed the acceptability ratings for each study to a value between 0 and 1 through min-max scaling, with 0 representing the &#8220;completely unacceptable&#8221; endpoint of the scale (or &#8220;ungrammatical&#8221; in binary judgment tasks), and 1 representing the &#8220;completely acceptable&#8221; endpoint (or &#8220;grammatical&#8221; in binary judgment tasks). For studies that directly reported the repetition number effects on acceptability ratings, we directly used the reported estimates, standard errors, and sample sizes in the meta-analysis. For the rest of the studies, we fit linear mixed-effects regression models predicting the adjusted acceptability ratings of each island-violating sentence type with a fixed effect of repetition number. Each model also included random by-participant and by-item intercepts and slopes for the fixed effect when the participant and item information was provided in the data files. In cases of non-convergence, random effects with the least variance were removed until convergence. We recorded the repetition number effect estimates and standard errors for meta-analysis.<xref ref-type="fn" rid="n12">12</xref></p>
<p>Using the <italic>metafor</italic> package (<xref ref-type="bibr" rid="B90">Viechtbauer, 2010</xref>) in R, we fit a random-effects meta-analytic model for studies testing each island effect type. Then, Cochran&#8217;s Q test (<xref ref-type="bibr" rid="B22">Cochran, 1950</xref>) was used to detect any cross-study heterogeneity. In case of significance, we fit a mixed-effects meta-analytic model to examine different moderators as possible sources of heterogeneity. Snyder (<xref ref-type="bibr" rid="B76">2022a</xref>) speculated that differences in scale types, total numbers of repetitions, and the use of context sentences<xref ref-type="fn" rid="n13">13</xref> could contribute to different findings in satiation experiments. Therefore, we included these three factors as moderators.</p>
<p>Finally, a funnel plot (a plot of standard errors against point estimates) was created for each island type. The Egger&#8217;s regression test (<xref ref-type="bibr" rid="B26">Egger et al., 1997</xref>) on funnel plot asymmetry was conducted to detect publication bias.</p>
</sec>
</sec>
<sec>
<title>2.2 Results</title>
<p>Below, we report the meta-analysis results for satiation studies examining the seven different island effects listed above: the Left Branch Condition (LBC), adjunct islands, the Complex NP Constraint (CNPC), subject islands, the <italic>that</italic>-trace construction, the <italic>want-for</italic> construction, and <italic>whether</italic>-islands.</p>
<sec>
<title>2.2.1 Satiation effect estimates</title>
<p><xref ref-type="fig" rid="F3">Figure 3</xref> summarizes the satiation effect estimates and 95% confidence intervals of the estimates obtained from the random-effects meta-analytic models for each island type. The effect sizes represent the estimated increase in acceptability on a 0&#8211;1 scale per repetition. A positive effect estimate with a 95% confidence interval not overlapping with 0 is taken as evidence for satiation. Based on the random-effects meta-analysis, we found significant evidence for the satiation of adjunct islands, the CNPC, subject islands, the <italic>that</italic>-trace construction, the <italic>want-for</italic> construction, and <italic>whether</italic>-islands. There was no evidence for the satiation of the LBC. <xref ref-type="fig" rid="F4">Figures 4</xref>, <xref ref-type="fig" rid="F5">5</xref>, <xref ref-type="fig" rid="F6">6</xref>, <xref ref-type="fig" rid="F7">7</xref>, <xref ref-type="fig" rid="F8">8</xref>, <xref ref-type="fig" rid="F9">9</xref>, <xref ref-type="fig" rid="F10">10</xref> are forest plots summarizing all selected studies that tested each of the seven island types.</p>
<fig id="F3">
<caption>
<p><bold>Figure 3:</bold> Forest plot summarizing estimates of satiation rate for all seven island types. Error bars represent 95% CIs.</p>
</caption>
<graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="glossapx-3-1-1425-g3.png"/>
</fig>
<fig id="F4">
<caption>
<p><bold>Figure 4:</bold> Forest plot of studies testing subject island satiation. Effect size captures acceptability increase per repetition. Error bars represent 95% CI, and the area of squares represents the weight given to each study based on its standard error and the estimated cross-study variance.</p>
</caption>
<graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="glossapx-3-1-1425-g4.png"/>
</fig>
<fig id="F5">
<caption>
<p><bold>Figure 5:</bold> Forest plot of studies testing the satiation of CNPC. Effect size captures acceptability increase per repetition. Error bars represent 95% CI, and the area of squares represents the weight given to each study based on its standard error and the estimated cross-study variance.</p>
</caption>
<graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="glossapx-3-1-1425-g5.png"/>
</fig>
<fig id="F6">
<caption>
<p><bold>Figure 6:</bold> Forest plot of studies testing <italic>whether</italic>-island satiation. Effect size captures acceptability increase per repetition. Error bars represent 95% CI, and the area of squares represents the weight given to each study based on its standard error and the estimated cross-study variance.</p>
</caption>
<graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="glossapx-3-1-1425-g6.png"/>
</fig>
<fig id="F7">
<caption>
<p><bold>Figure 7:</bold> Forest plot of studies testing adjunct island satiation. Effect size captures acceptability increase per repetition. Error bars represent 95% CI, and the area of squares represents the weight given to each study based on its standard error and the estimated cross-study variance.</p>
</caption>
<graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="glossapx-3-1-1425-g7.png"/>
</fig>
<fig id="F8">
<caption>
<p><bold>Figure 8:</bold> Forest plot of studies testing the satiation of the LBC. Effect size captures acceptability increase per repetition. Error bars represent 95% CI, and the area of squares represents the weight given to each study based on its standard error and the estimated cross-study variance.</p>
</caption>
<graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="glossapx-3-1-1425-g8.png"/>
</fig>
<fig id="F9">
<caption>
<p><bold>Figure 9:</bold> Forest plot of studies testing the satiation of the <italic>that</italic>-trace construction. Effect size captures acceptability increase per repetition. Error bars represent 95% CI, and the area of squares represents the weight given to each study based on its standard error and the estimated cross-study variance.</p>
</caption>
<graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="glossapx-3-1-1425-g9.png"/>
</fig>
<fig id="F10">
<caption>
<p><bold>Figure 10:</bold> Forest plot of studies testing the satiation of the <italic>want-for</italic> construction. Effect size captures acceptability increase per repetition. Error bars represent 95% CI, and the area of squares represents the weight given to each study based on its standard error and the estimated cross-study variance.</p>
</caption>
<graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="glossapx-3-1-1425-g10.png"/>
</fig>
<p>For the satiating island types, the estimated effect magnitudes may seem small, but are generally on par with contrasts reported in the past literature between the various island-violating sentence types and their corresponding grammatical controls. For example, for subject island sentences, we found a 0.0168 increase per repetition on a 0&#8211;1 scale, which translates to a 0.1008 increase on a 7-point Likert scale, or 1.008 after ten repetitions. Indeed, Chaves &amp; Dery (<xref ref-type="bibr" rid="B15">2014</xref>) reported a 1.065 contrast between subject island sentences and grammatical controls on a 7-point Likert scale, almost exactly the expected acceptability gain based on our estimates. For <italic>whether</italic>-island sentences, we found a 0.0303 increase per repetition on a 0&#8211;1 scale. The contrast between the mean ratings for whether-island sentences and the grammatical control, as reported in Lu et al. (<xref ref-type="bibr" rid="B56">2021</xref>), is 0.36 on a 0&#8211;1 scale, which again represents roughly the expected acceptability gain after 11&#8211;12 repetitions.<xref ref-type="fn" rid="n14">14</xref></p>
<p>In <xref ref-type="fig" rid="F3">Figure 3</xref>, there appear to be varying rates of satiation among the six island effect types that do satiate. This observation is confirmed by an analysis whereby we pooled the results of the satiating island types (all but the LBC) and fit a mixed-effects meta-analytic model predicting the rate of satiation with island type as a Helmert-coded predictor (ordered by satiation effect size estimates from small to large, as shown in <xref ref-type="fig" rid="F3">Figure 3</xref>). The analysis revealed significance for subject islands (<italic>z</italic> = 2.24, <italic>p</italic> &lt; 0.05) and <italic>whether</italic>-islands (<italic>z</italic> = 2.06, <italic>p</italic> &lt; 0.05), suggesting that these two island types show significantly higher satiation rates compared to the means of the previous levels. We can thus conclude that among the satiating island types, there are varying rates of satiation.<xref ref-type="fn" rid="n15">15</xref></p>
</sec>
<sec>
<title>2.2.2 Heterogeneity</title>
<p>The random-effects meta-analytic models revealed significant cross-study heterogeneity in three of the seven island types tested: subject islands, the CNPC, and <italic>whether</italic>-islands. Results from the Cochran&#8217;s Q test of heterogeneity for each island type are shown in <xref ref-type="table" rid="T3">Table 3</xref>. For the three islands showing significant heterogeneity, we fit mixed-effects meta-analytic models with three moderators to explore the sources of heterogeneity: context (whether or not a context sentence was provided in the experiment), the total number of repetitions, and scale type (binary vs. multi-point). Categorical moderators were sum-coded. The moderator analyses results are shown in <xref ref-type="table" rid="T4">Table 4</xref>. For subject islands and <italic>whether</italic>-islands, inclusion of a context sentence in the task resulted in greater satiation effects. None of the other moderator-island pairs reached significance.</p>
<p>For the subject island studies and the <italic>whether</italic>-island studies, we further conducted a subset analysis. For subject island studies, a random-effects meta-analytic model estimated a 0.0241 increase in acceptability per repetition (95% CI = [0.0103,0.0379]) when context is provided, and a 0.0109 increase per repetition (95% CI = [0.0059,0.0159]) when context is absent; for <italic>whether</italic>-island studies, a random-effects meta-analytic model model estimated a 0.0364 increase in acceptability per repetition (95% CI = [0.0113,0.0616]) when context is provided, and a 0.0201 increase in acceptability per repetition (95% CI = [&#8211;0.0108,0.0510]) when context is absent.</p>
<p>For all three island types, there was significant residual heterogeneity even when the three moderators were included in the meta-analytic model, suggesting that additional moderators might modulate the rate of satiation.</p>
</sec>
<sec>
<title>2.2.3 Publication bias</title>
<p>To assess whether these results are affected by publication bias, <xref ref-type="fig" rid="F11">Figures 11a&#8211;11g</xref> contain funnel plots for the selected studies of each island type. The funnel plots for CNPC and <italic>whether</italic>-island are visibly asymmetric.<xref ref-type="fn" rid="n16">16</xref> The asymmetry is further confirmed by Egger&#8217;s regression test results, as shown in <xref ref-type="table" rid="T2">Table 2</xref>. This suggests that there is possible publication bias among the CNPC and <italic>whether</italic>-island studies, so we should take the positive effect estimates for these two island types with a grain of salt.</p>
<table-wrap id="T2">
<caption>
<p><bold>Table 2:</bold> Egger&#8217;s regression test results for each island type. Marginally significant effects (suggesting possible publication bias) are shaded in light gray.</p>
</caption>
<table>
<thead>
<tr>
<td align="left" valign="top" rowspan="2"><bold>Island type</bold></td>
<td align="left" valign="top" colspan="2"><bold>Egger&#8217;s results</bold></td>
</tr>
<tr>
<td align="left" valign="top"><bold><italic>t</italic></bold></td>
<td align="left" valign="top"><bold><italic>p</italic></bold></td>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top">Subject Island</td>
<td align="left" valign="top">1.36</td>
<td align="left" valign="top">&lt;0.190</td>
</tr>
<tr>
<td align="left" valign="top" style="background-color:#d9d9d9;">Complex NP Constraint</td>
<td align="left" valign="top" style="background-color:#d9d9d9;">2.08</td>
<td align="left" valign="top" style="background-color:#d9d9d9;">&lt;0.059</td>
</tr>
<tr>
<td align="left" valign="top" style="background-color:#d9d9d9;">Whether-Island</td>
<td align="left" valign="top" style="background-color:#d9d9d9;">1.91</td>
<td align="left" valign="top" style="background-color:#d9d9d9;">&lt;0.081</td>
</tr>
<tr>
<td align="left" valign="top">Adjunct Island</td>
<td align="left" valign="top">&#8211;0.54</td>
<td align="left" valign="top">&lt;0.600</td>
</tr>
<tr>
<td align="left" valign="top">Left Branch Condition</td>
<td align="left" valign="top">0.61</td>
<td align="left" valign="top">&lt;0.564</td>
</tr>
<tr>
<td align="left" valign="top">That-trace Effect</td>
<td align="left" valign="top">0.74</td>
<td align="left" valign="top">&lt;0.495</td>
</tr>
<tr>
<td align="left" valign="top">Want-for Construction</td>
<td align="left" valign="top">0.39</td>
<td align="left" valign="top">&lt;0.720</td>
</tr>
</tbody>
</table>
</table-wrap>
<table-wrap id="T3">
<caption>
<p><bold>Table 3:</bold> Heterogeneity measures from random-effects meta-analytic models. Statistically significant effects are shaded in gray.</p>
</caption>
<table>
<thead>
<tr>
<td align="left" valign="top" rowspan="2"><bold>Island type</bold></td>
<td align="left" valign="top" colspan="3"><bold>Heterogeneity measures</bold></td>
</tr>
<tr>
<td align="left" valign="top"><bold>Cochran&#8217;s Q</bold></td>
<td align="left" valign="top"><bold><italic>p</italic></bold></td>
<td align="left" valign="top"><bold>I<sup>2</sup></bold></td>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top" style="background-color:#d9d9d9;">Subject Island</td>
<td align="left" valign="top" style="background-color:#d9d9d9;">346.4</td>
<td align="left" valign="top" style="background-color:#d9d9d9;">&lt;0.001</td>
<td align="left" valign="top" style="background-color:#d9d9d9;">94.06%</td>
</tr>
<tr>
<td align="left" valign="top" style="background-color:#d9d9d9;">Complex NP Constraint</td>
<td align="left" valign="top" style="background-color:#d9d9d9;">31.19</td>
<td align="left" valign="top" style="background-color:#d9d9d9;">&lt;0.006</td>
<td align="left" valign="top" style="background-color:#d9d9d9;">69.07%</td>
</tr>
<tr>
<td align="left" valign="top" style="background-color:#d9d9d9;">Whether-Island</td>
<td align="left" valign="top" style="background-color:#d9d9d9;">326.91</td>
<td align="left" valign="top" style="background-color:#d9d9d9;">&lt;0.001</td>
<td align="left" valign="top" style="background-color:#d9d9d9;">98.38%</td>
</tr>
<tr>
<td align="left" valign="top">Adjunct Island</td>
<td align="left" valign="top">8.03</td>
<td align="left" valign="top">&lt;0.783</td>
<td align="left" valign="top">0.00%</td>
</tr>
<tr>
<td align="left" valign="top">Left Branch Condition</td>
<td align="left" valign="top">2.21</td>
<td align="left" valign="top">&lt;0.978</td>
<td align="left" valign="top">0.00%</td>
</tr>
<tr>
<td align="left" valign="top">That-trace Construction</td>
<td align="left" valign="top">7.31</td>
<td align="left" valign="top">&lt;0.293</td>
<td align="left" valign="top">9.26%</td>
</tr>
<tr>
<td align="left" valign="top">Want-for Construction</td>
<td align="left" valign="top">3.28</td>
<td align="left" valign="top">&lt;0.657</td>
<td align="left" valign="top">0.00%</td>
</tr>
</tbody>
</table>
</table-wrap>
<table-wrap id="T4">
<caption>
<p><bold>Table 4:</bold> mixed-effects meta-analytic model results for island types showing significant heterogeneity in the random-effects analyses. Statistically significant effects are shaded in gray.</p>
</caption>
<table>
<thead>
<tr>
<td align="left" valign="top" rowspan="3"><bold>Island Type</bold></td>
<td align="left" valign="top" colspan="6"><bold>Moderators in the mixed-effects models</bold></td>
<td align="left" valign="top" rowspan="2" colspan="2"><bold>Residual heterogeneity</bold></td>
</tr>
<tr>
<td align="left" valign="top" colspan="2"><bold>Context inclusion</bold></td>
<td align="left" valign="top" colspan="2"><bold>Scale type</bold></td>
<td align="left" valign="top" colspan="2"><bold>Repetition number</bold></td>
</tr>
<tr>
<td align="left" valign="top"><bold><italic>t</italic></bold></td>
<td align="left" valign="top"><bold><italic>p</italic></bold></td>
<td align="left" valign="top"><bold><italic>t</italic></bold></td>
<td align="left" valign="top"><bold><italic>p</italic></bold></td>
<td align="left" valign="top"><bold><italic>t</italic></bold></td>
<td align="left" valign="top"><bold><italic>p</italic></bold></td>
<td align="left" valign="top"><bold>Cochran&#8217;s Q</bold></td>
<td align="left" valign="top"><bold><italic>p</italic></bold></td>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top">Subject Island</td>
<td align="left" valign="top" style="background-color:#d9d9d9;">2.37</td>
<td align="left" valign="top" style="background-color:#d9d9d9;">&lt;0.031</td>
<td align="left" valign="top">&#8211;1.17</td>
<td align="left" valign="top">&lt;0.259</td>
<td align="left" valign="top">1.02</td>
<td align="left" valign="top">&lt;0.321</td>
<td align="left" valign="top" style="background-color:#d9d9d9;">202.49</td>
<td align="left" valign="top" style="background-color:#d9d9d9;">&lt;0.001</td>
</tr>
<tr>
<td align="left" valign="top">Complext NP Constraint</td>
<td align="left" valign="top">1.12</td>
<td align="left" valign="top">&lt;0.287</td>
<td align="left" valign="top">&#8211;1.43</td>
<td align="left" valign="top">&lt;0.180</td>
<td align="left" valign="top">&#8211;0.08</td>
<td align="left" valign="top">&lt;0.936</td>
<td align="left" valign="top" style="background-color:#d9d9d9;">22.31</td>
<td align="left" valign="top" style="background-color:#d9d9d9;">&lt;0.023</td>
</tr>
<tr>
<td align="left" valign="top">Whether Island</td>
<td align="left" valign="top" style="background-color:#d9d9d9;">2.99</td>
<td align="left" valign="top" style="background-color:#d9d9d9;">&lt;0.014</td>
<td align="left" valign="top">&#8211;1.55</td>
<td align="left" valign="top">&lt;0.154</td>
<td align="left" valign="top">&#8211;0.34</td>
<td align="left" valign="top">&lt;0.738</td>
<td align="left" valign="top" style="background-color:#d9d9d9;">60.52</td>
<td align="left" valign="top" style="background-color:#d9d9d9;">&lt;0.001</td>
</tr>
</tbody>
</table>
</table-wrap>
<fig id="F11">
<caption>
<p><bold>Figure 11:</bold> Funnel plots for studies testing the satiation of each island type. Stars represent marginal significance in Egger&#8217;s test.</p>
</caption>
<graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="glossapx-3-1-1425-g11.png"/>
</fig>
</sec>
</sec>
</sec>
<sec>
<title>3. General discussion</title>
<sec>
<title>3.1 Summary</title>
<p>In this study, we conducted a meta-analysis of past experimental studies on the satiation of island-violating sentences in English. The results of this study provide answers to the following three questions. First, which types of islands reliably satiate? Second, which island types display heterogeneity in satiation, and which factors contribute to this heterogeneity? Third, is there evidence for a publication bias in the satiation literature?</p>
<p>To answer the first question, random effects meta-analytic models revealed significant acceptability increases for repetition in sentences violating constraints on adjunct islands, complex noun phrase islands, subject islands, the <italic>that</italic>-trace effect, the <italic>want-for</italic> construction, and <italic>whether</italic>-islands. In contrast, the models did not reveal evidence of acceptability increases for sentences violating the Left Branch Condition (see <xref ref-type="fig" rid="F3">Figure 3</xref>).</p>
<p>To answer the second question, significant cross-study heterogeneity was detected among the CNPC studies, the subject island studies, and the <italic>whether</italic>-island studies. Following speculation by Snyder (<xref ref-type="bibr" rid="B76">2022a</xref>), we tested the contribution of three moderators (presence of context sentences in the experiment, total number of repetitions, and the scale type) to the heterogeneity. For CNPC studies, there was no evidence for any of the moderators modulating satiation; for subject island studies and <italic>whether</italic>-island studies, the presence of a context sentence increased the rate of satiation, while the other two moderators did not reach significance. For all three groups of studies, residual heterogeneity persisted even when the three moderators were included in the mixed-effects model, suggesting that additional moderators contribute to cross-study heterogeneity.</p>
<p>One such moderator may be the number of fillers. The increase in acceptability of the critical items due to exposure might gradually decay when participants see many unrelated filler items, similar to the observed effect of number of intervening items between prime and target on the strength of priming effects. Thus, the rate of satiation might be smaller when more filler items are included in the experiment. However, since not all selected studies reported filler information in the original papers or in the data files shared by the authors, we could not include the number of fillers as a moderator. Another factor that could affect satiation is the inclusion of multiple island types in the same experiment. It has been demonstrated that exposure to one island-violating sentence type leads to a change in the acceptability of another island-violating sentence type (<xref ref-type="bibr" rid="B58">Lu et al., 2022</xref>).<xref ref-type="fn" rid="n17">17</xref> Therefore, it is possible that when multiple island sentence types are tested together in a single experiment, they might influence each other&#8217;s rate of satiation. Cross-study heterogeneity could then arise as a result of different studies testing different sets of island sentence types.</p>
<p>To answer the third question, there is possible publication bias favoring the studies reporting significant satiation for sentences violating the CNPC and the <italic>whether</italic>-island. However, the evidence is not strong and is based on marginally significant results from Egger&#8217;s regression test of funnel plot asymmetry. We did not find a funnel plot asymmetry in any other group of studies, suggesting that there is no evidence for a publication bias in those groups of studies. However, we should note that these groups tended to also be the ones with fewer studies. It is possible that for island types with fewer studies, we might not have had the statistical power to detect publication bias even if the bias exists, creating a false picture that there is no publication bias in those groups of studies. An exception is subject islands, which have the largest number of studies devoted to them and yet didn&#8217;t show evidence of publication bias.</p>
</sec>
<sec>
<title>3.2 Implications</title>
<p>The results of this meta-analysis are valuable in at least four different ways: in the debate over grammatical vs. processing accounts of islands, in the debate between different linking hypotheses for satiation, in the debate over whether subject and adjunct islands form a natural class in the taxonomy of islands, and in revealing the varying rates of satiation of different islands as a future direction for research.</p>
<p>First, the results may inform the debate over grammatical and processing accounts of islands. As discussed in Section 1, it is often implicitly assumed that when a degraded sentence type satiates, the source of the degradation should come from extra-grammatical factors like high working memory burden (<xref ref-type="bibr" rid="B41">Hofmeister et al., 2013</xref>; <xref ref-type="bibr" rid="B43">Hofmeister &amp; Sag, 2010</xref>) or low frequency (<xref ref-type="bibr" rid="B15">Chaves &amp; Dery, 2014</xref>, <xref ref-type="bibr" rid="B16">2019</xref>). Assuming that this linking hypothesis is accurate (and we shall return to the possibility that it is not), the results reported here can be used to inform theories of island effects: the reliable satiation effects for adjunct islands, CNPC, subject islands, the <italic>that</italic>-trace construction, the <italic>want-for</italic> construction, and <italic>whether</italic>-islands suggests they should be considered grammatical but degraded due to processing factors. In contrast, the LBC does not satiate, and therefore should be considered ungrammatical. These grammaticality statuses pose a challenge to syntactic theories that predict the ungrammaticality of the satiating island types. These include the Government and Binding (GB) theory, which attributes island effects to grammatical constraints like the Subjacency Condition and the Empty Category Principle (<xref ref-type="bibr" rid="B21">Chomsky, 1986</xref>; <xref ref-type="bibr" rid="B44">Huang, 1982</xref>), and syntactic theories under the minimalist program that attribute island effects to the cyclic nature of spell-out and linearization (<xref ref-type="bibr" rid="B30">Fox &amp; Pesetsky, 2005</xref>; <xref ref-type="bibr" rid="B62">Nunes &amp; Uriagereka, 2000</xref>). In contrast, our results are, in general, compatible with syntactic theories without non-local syntactic constraints. For example, in certain versions of the Head-driven Phrase Structure Grammar (HPSG) (<xref ref-type="bibr" rid="B5">Boas &amp; Sag, 2012</xref>; <xref ref-type="bibr" rid="B59">Michaelis, 2013</xref>), only island effects that can be framed in terms of local constraints are predicted to exist without arbitrary stipulations of filtering constraints. Most island-violating sentences, including the ones that reliably satiate according to this meta-analysis, are predicted to be grammatical in this framework (see Chaves &amp; Putnam (<xref ref-type="bibr" rid="B17">2020</xref>) for a detailed discussion of the predicted island effects under this framework). In contrast, the LBC, where we found no evidence for satiation, can be captured in HPSG by an independently motivated local constraint requiring that only elements in the <sc>arg(ument)-st(ructure)</sc> feature list of a head can appear in the <sc>gap</sc> feature list of the same head. Possessors and modifiers are not part of the <sc>arg-st</sc> list of an N head, and thus cannot appear in the <sc>gap</sc> list of N (i.e., cannot be extracted from an NP, <xref ref-type="bibr" rid="B17">Chaves &amp; Putnam, 2020</xref>; <xref ref-type="bibr" rid="B70">Runner et al., 2006</xref>; <xref ref-type="bibr" rid="B72">Sag, 2012</xref>). Nevertheless, one should note that the <italic>that</italic>-trace construction and the <italic>want-for</italic> construction are largely left out of the debate between processing-level and grammar-level accounts of island effects, and processing-based accounts of their pre-satiation degradedness are yet to be worked out.<xref ref-type="fn" rid="n18">18</xref> This may be particularly challenging for the <italic>want-for</italic> construction, where the declarative form (example (2)) without the long-distance dependency is also considered by many speakers to be degraded, suggesting that the unacceptability of the <italic>want-for</italic> construction cannot be attributed to a hard-to-process dependency.</p>
<list list-type="gloss">
<list-item>
<list list-type="wordfirst">
<list-item><p>(2)</p></list-item>
</list>
</list-item>
<list-item>
<list list-type="sentence-gloss">
<list-item>
<list list-type="final-sentence">
<list-item><p>??I want for Mary to buy a cake.</p></list-item>
</list>
</list-item>
</list>
</list-item>
</list>
<p>As for the <italic>that</italic>-trace construction, past accounts mostly attributed its degradedness to syntactic constraints (e.g., the anti-locality constraint) or phonological constraints (e.g., a phonological requirement that a complementizer cannot be linearly adjacent to a gap).<xref ref-type="fn" rid="n19">19</xref> It remains unclear how the <italic>that</italic>-trace effect can be captured by a processing-level explanation. If one believes that processing-level accounts for the <italic>want-for</italic> and the <italic>that</italic>-trace constructions are implausible, the satiation of these two sentence types may also be taken as evidence against the linking hypothesis that satiation reflects grammaticality.</p>
<p>Second, the discussion up to this point assumes the linking hypothesis that grammaticality decides the satiability of degraded sentences. However, this hypothesis is not unchallenged. Other factors have been claimed to affect the satiability of sentences, including whether the grammatical constraint violated is part of Universal Grammar (UG) (<xref ref-type="bibr" rid="B9">Braze, 2002</xref>; <xref ref-type="bibr" rid="B40">Hiramatsu, 2001</xref>; <xref ref-type="bibr" rid="B75">Snyder, 2000</xref>), the surface similarity with a grammatical alternative (<xref ref-type="bibr" rid="B80">Sprouse, 2007</xref>), and sentence interpretability (<xref ref-type="bibr" rid="B31">Francom, 2009</xref>). Instead of assuming a particular linking hypothesis under which to test theories of island effects, one can also use the meta-analysis results to inform the linking hypothesis itself. For example, the hypothesis that grammatical principles in UG determine satiability is rejected by our results. Under this hypothesis, the LBC, which is the only non-satiating island type among the ones investigated, should be a principle in the UG. However, the LBC is in fact subject to variation cross-linguistically. Left branch extraction (extraction of modifiers or possessors out of an NP) is permitted in many Slavic languages (<xref ref-type="bibr" rid="B7">Bo&#353;kovi&#263;, 2005</xref>). For example, Serbo-Croatian allows the equivalent of &#8220;Whose<italic><sub>i</sub></italic> does Petko like t<italic><sub>i</sub></italic> car?&#8221; as shown in (3). This shows that the LBC cannot be a grammatical principle encoded in UG, thus rejecting the hypothesis that satiation diagnoses UG principles.</p>
<list list-type="gloss">
<list-item>
<list list-type="wordfirst">
<list-item><p>(3)</p></list-item>
</list>
</list-item>
<list-item>
<list list-type="sentence-gloss">
<list-item>
<list list-type="final-sentence">
<list-item><p>Left Branch Extraction in Serbo-Croation&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;(<xref ref-type="bibr" rid="B7">Bo&#353;kovi&#263;, 2005, p. 3</xref>)</p></list-item>
</list>
</list-item>
<list-item>
<list list-type="word">
<list-item><p>&#268;ija<italic><sub>i</sub></italic></p></list-item>
<list-item><p>Whose<italic><sub>i</sub></italic></p></list-item>
</list>
<list list-type="word">
<list-item><p>xaresva</p></list-item>
<list-item><p>like</p></list-item>
</list>
<list list-type="word">
<list-item><p>Petko</p></list-item>
<list-item><p>Petko</p></list-item>
</list>
<list list-type="word">
<list-item><p>t<italic><sub>i</sub></italic></p></list-item>
<list-item><p>t<italic><sub>i</sub></italic></p></list-item>
</list>
<list list-type="word">
<list-item><p>kola?</p></list-item>
<list-item><p>car</p></list-item>
</list>
</list-item>
<list-item>
<list list-type="final-sentence">
<list-item><p>&#8220;Whose car does Petko like?&#8221;</p></list-item>
</list>
</list-item>
</list>
</list-item>
</list>
<p>Consider also the linking hypothesis that satiation is underlyingly linguistic adaptation, whereby participants update their beliefs about the frequency distribution of degraded sentence types throughout acceptability judgment experiments (<xref ref-type="bibr" rid="B56">Lu et al., 2021</xref>, <xref ref-type="bibr" rid="B58">2022</xref>). Under this proposal, participants should be able to update their expectations for any given sentence type whose underlying linguistic representations can be recovered. This predicts that any sentence type, with the exception of word-salad sentences from which no abstract linguistic representation can be recovered, should demonstrate satiation. However, our results show that the LBC sentences resist satiation altogether, which is not predicted by the vanilla version of the adaptation-based linking hypothesis. It is likely that there are other gate-keeping factors at play, restricting the satiation of an otherwise perfectly representable structure.</p>
<p>One possible candidate for such gate-keeping factors is the availability of grammatical alternatives: when the intended meaning of a sentence can be expressed by a more acceptable alternative sentence, satiation of the sentence is suppressed, perhaps because the participants do not adapt to sentences produced by hypothetically non-cooperative speakers. Among all seven sentence types investigated, the LBC sentences are the only type with a clear meaning-equivalent acceptable alternative. For example, the unacceptable LBC-violating sentence (4a) has the meaning-equivalent acceptable alternative (4b).</p>
<list list-type="gloss">
<list-item>
<list list-type="wordfirst">
<list-item><p>(4)</p></list-item>
</list>
<list list-type="wordfirst">
<list-item><p>a.</p></list-item>
</list>
</list-item>
<list-item>
<list list-type="sentence-gloss">
<list-item>
<list list-type="final-sentence">
<list-item><p>*How many did John buy books?</p></list-item>
</list>
</list-item>
</list>
</list-item>
</list>
<list list-type="gloss">
<list-item>
<list list-type="wordfirst">
<list-item><p>&#160;</p></list-item>
</list>
<list list-type="wordfirst">
<list-item><p>b.</p></list-item>
</list>
</list-item>
<list-item>
<list list-type="sentence-gloss">
<list-item>
<list list-type="final-sentence">
<list-item><p>&#160;&#160;How many books did John buy?</p></list-item>
</list>
</list-item>
</list>
</list-item>
</list>
<p>Whether the availability of acceptable alternatives is indeed the reason why the LBC sentences resist satiation is beyond the scope of the current study, but further studies should test this possibility.</p>
<p>Third, our results also have implications for the debate regarding whether subject and adjunct islands are reducible to the same underlying constraint. In syntactic theories, among the various types of island effects, adjunct islands and subject islands are traditionally considered to form a natural class. For example, Huang (<xref ref-type="bibr" rid="B44">1982</xref>) attributes both adjunct and subject island effects to a single syntactic principle: the Condition on Extraction Domains (CED), which states that constituents that are not properly governed restrict extraction from within. Subject DPs and adjuncts are not properly governed, and therefore are both CED islands.<xref ref-type="fn" rid="n20">20</xref> Chomsky (<xref ref-type="bibr" rid="B21">1986</xref>), which aims to provide an analysis for all island effects using the concept of <italic>barriers</italic>, also grouped subject and adjunct islands together. Movements out of adjuncts and subjects need to cross two barriers, whereas movements out of other islands (e.g., <italic>whether</italic>-islands, complex NPs) cross only one barrier. Studies including Hiramatsu (<xref ref-type="bibr" rid="B40">2001</xref>) and Stepanov (<xref ref-type="bibr" rid="B84">2007</xref>) question Huang&#8217;s (<xref ref-type="bibr" rid="B44">1982</xref>) and Chomsky&#8217;s (<xref ref-type="bibr" rid="B21">1986</xref>) accounts on the grounds that subject island sentences satiate while adjunct island sentences do not. Assuming a linking hypothesis under which structures with a common source of unacceptability should show a similar satiation profile (<xref ref-type="bibr" rid="B9">Braze, 2002</xref>; <xref ref-type="bibr" rid="B35">Goodall, 2011</xref>; <xref ref-type="bibr" rid="B75">Snyder, 2000</xref>), we would expect subject and adjunct islands to either both satiate or both resist satiation, contrary to Hiramatsu&#8217;s (<xref ref-type="bibr" rid="B40">2001</xref>) observation. However, as is evident in the current meta-analysis, there is reliable evidence that both subject and adjunct island sentences satiate. Although this result cannot distinguish between the CED or the barriers account, at least it provides sufficient grounds for rejecting Hiramatsu&#8217;s (<xref ref-type="bibr" rid="B40">2001</xref>) counterargument.</p>
<p>Fourth, our results point to a future direction of research. As mentioned in Section 2.2.1, there appear to be varying rates of satiation among the satiating island types. The differences in the rates of satiation might signal differences in the linguistic properties underlying these sentence types, and could potentially become a useful diagnostic tool for experimental syntacticians. Differences in rates of satiation could reflect different sources of unacceptability (see <xref ref-type="bibr" rid="B35">Goodall, 2011</xref>, for a similar proposal). Further research is needed to determine which factors govern the rate of satiation.</p>
</sec>
<sec>
<title>3.3 Limitations</title>
<p>Finally, we would like to acknowledge several limitations of the current study.</p>
<p>First, the results of the Egger&#8217;s test provide evidence for publication bias only among the CNPC and <italic>whether</italic>-island studies. This does not suggest that there is no publication bias for the other island types. It is possible that the Egger&#8217;s tests we conducted simply lack the statistical power to detect publication bias for the island types with fewer studies (e.g., the <italic>that</italic>-trace construction and the <italic>want-for</italic> construction both have fewer than 10 studies).</p>
<p>Second, the current meta-analysis reports results on the satiation of island-violating sentences (i.e., the increase in acceptability ratings for sentences that contain island violations), as opposed to the amelioration of island constraints (i.e., the amelioration of the acceptability degradation induced by violating an island constraint). This is because the current meta-analysis is constrained by the design of early satiation experiments that did not include the relevant grammatical control conditions that would enable us to probe for the amelioration of island constraints. However, we should note that the satiation of an island-violating sentence type does not necessarily reflect any change in the relevant island constraint, which is only one of various possible sources of degradation for the tested sentence type.</p>
<p>Below, we would like to point to a possible future direction for satiation researchers interested in teasing these two concepts apart. Recent experimental syntax studies on islands have largely adopted the &#8220;factorial design of measuring island effects&#8221; (<xref ref-type="bibr" rid="B32">Fukuda et al., 2022</xref>; <xref ref-type="bibr" rid="B46">Keshev &amp; Meltzer-Asscher, 2019</xref>; <xref ref-type="bibr" rid="B47">Kim &amp; Goodall, 2016</xref>; <xref ref-type="bibr" rid="B51">Ko et al., 2019</xref>; <xref ref-type="bibr" rid="B52">Kush et al., 2018</xref>, <xref ref-type="bibr" rid="B53">2019</xref>; <xref ref-type="bibr" rid="B57">Lu et al., 2020</xref>; <xref ref-type="bibr" rid="B82">Sprouse et al., 2016</xref>, <xref ref-type="bibr" rid="B83">2012</xref>; <xref ref-type="bibr" rid="B85">Stepanov et al., 2018</xref>, <italic>inter alia</italic>). Consider a CNPC sentence such as (5).</p>
<list list-type="gloss">
<list-item>
<list list-type="wordfirst">
<list-item><p>(5)</p></list-item>
</list>
</list-item>
<list-item>
<list list-type="sentence-gloss">
<list-item>
<list list-type="final-sentence">
<list-item><p>*What did you make the claim that John bought?</p></list-item>
</list>
</list-item>
</list>
</list-item>
</list>
<p>The degraded status of (5) could be due to any of the following factors: (a) a long-distance dependency crossing a clausal boundary, which may be cognitively taxing to process; (b) a Complex NP embedded clause structure, which may be structurally infrequent; (c) a special penalty for having a long-distance dependency crossing a Complex NP embedded clause structure (i.e., the violation of an island constraint). Under the factorial design of measuring island effects, these potential sources of degradation are teased apart using a 2 &#215; 2 factorial design manipulating dependency distance (movement from embedded clause vs. movement from matrix) and embedded clause structure (island structure vs. non-island structure). An example set of stimuli is shown in (6), adapted from Sprouse et al. (<xref ref-type="bibr" rid="B83">2012</xref>).</p>
<list list-type="gloss">
<list-item>
<list list-type="wordfirst">
<list-item><p>(6)</p></list-item>
</list>
</list-item>
<list-item>
<list list-type="sentence-gloss">
<list-item>
<list list-type="final-sentence">
<list-item><p>An example stimuli set under the factorial design of probing for island effects</p></list-item>
</list>
</list-item>
</list>
</list-item>
</list>
<list list-type="gloss">
<list-item>
<list list-type="wordfirst">
<list-item><p>&#160;</p></list-item>
</list>
<list list-type="wordfirst">
<list-item><p>a.</p></list-item>
</list>
</list-item>
<list-item>
<list list-type="sentence-gloss">
<list-item>
<list list-type="final-sentence">
<list-item><p><sc>non-island&#124;matrix</sc>: Who claimed that John bought a car?</p></list-item>
</list>
</list-item>
</list>
</list-item>
</list>
<list list-type="gloss">
<list-item>
<list list-type="wordfirst">
<list-item><p>&#160;</p></list-item>
</list>
<list list-type="wordfirst">
<list-item><p>b.</p></list-item>
</list>
</list-item>
<list-item>
<list list-type="sentence-gloss">
<list-item>
<list list-type="final-sentence">
<list-item><p><sc>non-island&#124;embedded</sc>: What did you claim that John bought?</p></list-item>
</list>
</list-item>
</list>
</list-item>
</list>
<list list-type="gloss">
<list-item>
<list list-type="wordfirst">
<list-item><p>&#160;</p></list-item>
</list>
<list list-type="wordfirst">
<list-item><p>c.</p></list-item>
</list>
</list-item>
<list-item>
<list list-type="sentence-gloss">
<list-item>
<list list-type="final-sentence">
<list-item><p><sc>island&#124;matrix</sc>: Who made the claim that John bought a car?</p></list-item>
</list>
</list-item>
</list>
</list-item>
</list>
<list list-type="gloss">
<list-item>
<list list-type="wordfirst">
<list-item><p>&#160;</p></list-item>
</list>
<list list-type="wordfirst">
<list-item><p>d.</p></list-item>
</list>
</list-item>
<list-item>
<list list-type="sentence-gloss">
<list-item>
<list list-type="final-sentence">
<list-item><p><sc>island&#124;embedded</sc>: What did you make the claim that John bought?</p></list-item>
</list>
</list-item>
</list>
</list-item>
</list>
<p>If the island constraint violation contributes unacceptability, we should detect it as an interaction effect between dependency distance and clause structure, where the dependency distance penalty is larger in the island conditions than in the non-island conditions. This factorial design of measuring island effects can be valuable for future research on the satiation of island effects. If the island constraint itself is affected by repeated exposure, we should expect a three-way interaction of dependency distance, clause structure, and presentation order, in the direction where the super-additive interaction of dependency distance and clause structure decreases as presentation order increases. This would serve as a more rigorous test for whether the satiation of island-violating sentences truly reflects the amelioration of the underlying island constraints.</p>
</sec>
</sec>
<sec>
<title>4. Conclusion</title>
<p>In this article, we present a meta-analysis of past experimental studies investigating the satiation of island-violating sentences. The meta-analysis provides effect size estimates for the satiation rates of different types of island-violating sentences, identifies the island types that display heterogeneity in satiation and the factors that modulate such heterogeneity, and identifies publication bias in the literature.</p>
<p>On a broader level, the current study also demonstrates that meta-analysis, already widely employed in disciplines such as medicine and psychology, can be a valuable research tool for linguists. A common issue for quantitative studies in linguistics is low statistical power due to small sample sizes or poor research design, giving rise to mixed findings and non-replications (<xref ref-type="bibr" rid="B65">Prasad &amp; Linzen, 2021</xref>; <xref ref-type="bibr" rid="B79">S&#246;nning &amp; Werner, 2021</xref>; <xref ref-type="bibr" rid="B88">Vasishth &amp; Gelman, 2021</xref>; <xref ref-type="bibr" rid="B89">Vasishth et al., 2018</xref>). Moreover, academic journals typically discourage the publication of null experimental results, leading to widespread publication bias (<xref ref-type="bibr" rid="B68">Roettger, 2021</xref>; <xref ref-type="bibr" rid="B89">Vasishth et al., 2018</xref>). The current study shows that meta-analysis can address these issues by synthesizing results from individual studies, even if they are underpowered, without the need for new experiments with substantially larger sample sizes. Moreover, as demonstrated, meta-analysis can help identify publication bias. Overall, meta-analytic methods can improve the quality and rigor of quantitative research in linguistics and should be considered an essential component of the linguistic research toolkit.</p>
</sec>
</body>
<back>
<fn-group>
<fn id="n1"><p>In the current study, we use the terms <italic>islands</italic> and <italic>island effects</italic> purely descriptively, and do not intend them to entail that the various sentence types labeled as such share the same underlying violation.</p></fn>
<fn id="n2"><p>Cf. Phillips (<xref ref-type="bibr" rid="B64">2006</xref>), Sprouse et al. (<xref ref-type="bibr" rid="B83">2012</xref>), and Yoshida et al. (<xref ref-type="bibr" rid="B91">2014</xref>) for experimental evidence against the processing-based accounts of island effects.</p></fn>
<fn id="n3"><p>For discussions of this assumption and alternatives, see Snyder (<xref ref-type="bibr" rid="B75">2000</xref>), Hiramatsu (<xref ref-type="bibr" rid="B40">2001</xref>), Braze (<xref ref-type="bibr" rid="B9">2002</xref>), Hofmeister &amp; Sag (<xref ref-type="bibr" rid="B43">2010</xref>), Hofmeister et al. (<xref ref-type="bibr" rid="B41">2013</xref>), and Goodall (<xref ref-type="bibr" rid="B35">2011</xref>).</p></fn>
<fn id="n4"><p>The term <italic>syntactic satiation</italic> was first used in Stromswold (<xref ref-type="bibr" rid="B86">1986</xref>), and was defined as the decrease in certainty in participants&#8217; judgments for sentences after repeated exposure. This is different from the working definition for satiation that we adopt: following the various studies since Snyder (<xref ref-type="bibr" rid="B75">2000</xref>), we define syntactic satiation as the increase in acceptability rating throughout repeated exposure.</p></fn>
<fn id="n5"><p>Sprouse (<xref ref-type="bibr" rid="B81">2009</xref>) suggested a linking hypothesis where satiation is considered the result of an &#8220;equalization response strategy&#8221; employed by participants: they tend to balance the number of positive and negative responses. If an experiment contains an overwhelming number of degraded sentences, participants will gradually increase the number of positive ratings throughout the experiment to maintain a balance between positive and negative ratings. Under Sprouse&#8217;s (<xref ref-type="bibr" rid="B81">2009</xref>) linking hypothesis, satiation should not contribute to our understanding of island effects (or any linguistic phenomenon) at all, because the equalization response strategy that underlies satiation is non-linguistic. However, there is now abundant evidence suggesting that satiation effects cannot be reduced to only the equalization response strategy (<xref ref-type="bibr" rid="B15">Chaves &amp; Dery, 2014</xref>; <xref ref-type="bibr" rid="B23">Crawford, 2012</xref>; <xref ref-type="bibr" rid="B31">Francom, 2009</xref>; <xref ref-type="bibr" rid="B56">Lu et al., 2021</xref>, <xref ref-type="bibr" rid="B58">2022</xref>). Thus, we will not further discuss the equalization response strategy in the current study.</p></fn>
<fn id="n6"><p>These are not to be confused with fixed-effects and mixed-effects regression models.</p></fn>
<fn id="n7"><p>There are also more sophisticated models available for testing publication bias. See Hedges &amp; Vevea (<xref ref-type="bibr" rid="B39">2005</xref>) for examples of non-graphical methods of detecting publication bias.</p></fn>
<fn id="n8"><p>The majority of studies on syntactic satiation utilized some form of the closed rating scale (e.g., 5/7-point Likert scale, 0&#8211;1 continuous slider scale). We did not include open-scale acceptability judgment experiments (e.g., magnitude estimation experiments), because there is no well-justified way of converting such scales to a closed interval such that the results can be aggregated with the other studies for meta-analytic purposes. Five experiments from Sprouse (<xref ref-type="bibr" rid="B81">2009</xref>) were excluded for this reason. These five experiments each tested subject islands, adjunct islands, <italic>whether</italic>-islands, and CNPC with and without context sentences. The subject island and the adjunct island experiments have 14 repetitions, while the other three experiments have 10 repetitions. None of the five reported a satiation effect.</p></fn>
<fn id="n9"><p>As noted by Snyder (<xref ref-type="bibr" rid="B76">2022a</xref>), the CNPC condition in Francom&#8217;s (<xref ref-type="bibr" rid="B31">2009</xref>) Experiment 1 includes several sentence tokens that, in fact, do not contain CNPC violations. Therefore, the CNPC satiation results in that study might be confounded. However, we still include all the data from Francom (<xref ref-type="bibr" rid="B31">2009</xref>) for systematicity. Note that removing the data from Francom (<xref ref-type="bibr" rid="B31">2009</xref>) does not lead to any qualitative change in the meta-analytic results.</p></fn>
<fn id="n10"><p>We should note that there is a crucial difference between the satiation of island-violating sentences and the amelioration of island violations, two concepts that are often confused in the satiation literature. Without including the relevant grammatical control sentences in the analysis, we can only test whether island-violating sentences satiate, which may or may not reflect whether the acceptability penalties due to island effects are ameliorated. We shall return to this issue in Section 3.</p></fn>
<fn id="n11"><p>There is considerable debate in the literature about whether to report standardized effect sizes or effects in the original units in meta-analyses. One recommendation that has emerged is that, if the original units are meaningful, these can be more helpful (<xref ref-type="bibr" rid="B3">Baguley, 2009</xref>; <xref ref-type="bibr" rid="B45">Kelley &amp; Preacher, 2012</xref>). In particular, the issue is that standardized effect sizes are standardized with respect to the variance in the data. Therefore, if the variance is different for different studies for reasons unrelated to the critical conditions (e.g., the types and the amount of filler sentences included), there would be different standardized effect sizes even when the actual magnitude of the effect is the same (i.e., a &#8220;reliability paradox&#8221;). We are especially worried about this in the case of satiation effects.</p></fn>
<fn id="n12"><p>An anonymous reviewer pointed out that a few of the studies show satiation effects based on the effect estimates we obtained, but the original authors reported no satiation effects. This discrepancy is the result of either the current study and the original studies having used different working definitions for satiation, or because the original studies used statistical models and hypothesis testing methods different from ours, which we cannot implement either due to the lack of relevant information in the data files available or due to the need to remain consistent and use the same model to obtain satiation effect estimates for all studies included in the meta-analysis.</p></fn>
<fn id="n13"><p>Context sentences used in satiation experiments are usually just the declarative form of the interrogative test sentences, presented along with the test sentences to participants. We follow Snyder (<xref ref-type="bibr" rid="B76">2022a</xref>) in calling these sentences &#8220;context sentences&#8221;.</p></fn>
<fn id="n14"><p>These estimates should be taken with a grain of salt: the estimated acceptability gains are calculated based on the assumption that the effect of trial order is linear. This is likely to be an incorrect assumption &#8211; satiation effects tend to be strongest early on and plateau later in the experiment (<xref ref-type="bibr" rid="B29">Fine et al., 2010</xref>, <xref ref-type="bibr" rid="B28">2013</xref>). In this case, we could be overestimating the acceptability increase after 11&#8211;12 repetitions.</p></fn>
<fn id="n15"><p>Note that we are not arguing that subject islands or <italic>whether</italic>-islands have a special status, nor are we arguing for a grouping among the island types with subject island and <italic>whether</italic>-islands being the breakpoints. We simply take this result as evidence for varying rates of satiation among the island types investigated.</p></fn>
<fn id="n16"><p>The funnel plot for subject island also appears asymmetric, but Egger&#8217;s test does not show significance. The high number of studies that fall outside the funnel area in Figure 11a could result from high cross-study heterogeneity.</p></fn>
<fn id="n17"><p>Snyder (<xref ref-type="bibr" rid="B75">2000</xref>, <xref ref-type="bibr" rid="B76">2022a</xref>) also tested the generalization of satiation effects between different lexical realizations of the same island type (e.g., between CNPC sentences with the matrix predicates <italic>believe the claim</italic> and <italic>accept the idea</italic>), but reported mixed results.</p></fn>
<fn id="n18"><p>As noted earlier, these two sentence types are not traditionally considered islands in the syntax literature, but we follow Snyder (<xref ref-type="bibr" rid="B75">2000</xref>) and other previous work in the satiation literature in labeling them as island structures for the purpose of discussion.</p></fn>
<fn id="n19"><p>For a comprehensive review of past proposals for the <italic>that</italic>-trace effect, see Pesetsky (<xref ref-type="bibr" rid="B63">2017</xref>).</p></fn>
<fn id="n20"><p>See Nunes &amp; Uriagereka (<xref ref-type="bibr" rid="B62">2000</xref>) for a more modern rendering of the CED in the minimalist framework.</p></fn>
</fn-group>
<sec>
<title>Data accessibility statement</title>
<p>All data files and analysis scripts are available at <ext-link ext-link-type="uri" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="https://osf.io/arj8c/">https://osf.io/arj8c/</ext-link>.</p>
</sec>
<sec>
<title>Acknowledgements</title>
<p>We would like to thank the authors of the analyzed studies for kindly making their data files available. Thanks to three anonymous reviewers, Rui Chaves, Dan Lassiter, William Snyder, Tom Wasow, members of the Interactive Language Processing Lab (The ALPS Lab) at Stanford University, and the audiences at LSA 2023 and CAMP 2023 for their valuable comments and feedback.</p>
</sec>
<sec>
<title>Competing interests</title>
<p>The authors have no competing interests to declare.</p>
</sec>
<sec>
<title>Author contributions</title>
<p>All authors contributed to the conceptualization of the study. JL acquired the data sets and conducted the analysis. All three authors contributed to the drafting and revision of the paper.</p>
</sec>
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