Second chances in antecedent retrieval: The processing of reflexives in two types of reconstruction environments
Bibliographic record
Abstract
Abstract A body of psycholinguistic research shows that structural constraints play a large role in guiding anaphora resolution in the early moments of processing (Nicol and Swinney 1989; Harris et al. 2000; Sturt 2003; Kazanina et al. 2007; Xiang et al. 2009; Chow et al. 2014). Omaki (2010) and Omaki et al. (2019) report on an interesting case where reflexives in wh-predicate fronting constructions launch a search that is not structurally guided. We further investigate this phenomenon, by asking whether non-structurally guided retrievals of this sort result in comprehenders ever committing to ungrammatical antecedents, perhaps as a ‘lingering’ interpretation of the sort found with garden path sentences (Christianson et al. 2001; Ferreira et al. 2001; Slattery et al. 2013). In two forced-choice studies, we find evidence that ungrammatical dependencies resulting from a non-structural search are sometimes maintained in offline comprehension, particularly with a more demanding task. We then probe the incremental processing that follows non-structurally guided retrieval, asking if and when the processor initiates a renewed search. In a self-paced reading experiment, we show that the processor continues its search for an antecedent very soon after retrieving a non-structurally guided antecedent. Surprisingly, however, we found a similar processing profile in cases where a structurally licensed antecedent was already encountered. While it has been recently shown that cataphoric pronouns persist in an antecedent search after a failed retrieval (Giskes and Kush 2021), our results suggest that when reflexives locate a preceding antecedent – by either a structural or non-structural search – this does not terminate further consideration of a different dependency. We consider these data in light of the comparison between cataphoric elements and wh-fillers in launching an active search to complete a dependency.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".