Indeterminate and Enriched Propositions in Context Linger: Evidence From an Eye-Tracking False Memory Paradigm
Bibliographic record
Abstract
A sentence such asWe finished the paperis indeterminate with regards to what we finished doing with the paper. Indeterminate sentences constitute a test case for two major issues regarding language comprehension: (1) how we compose sentence meaning; and (2) what is retained in memory about what we read in context over time. In an eye-tracking experiment, participants read short stories that were unexpectedly followed by one of three recognition probes: (a) an indeterminate sentence (Lisa began the book), that is identical to the one in the story; (b) an enriched but false probe (Lisa began reading the book); and (c) a contextually unrelated probe (Lisa began writing the book). The probes were presented either at the offset of the original indeterminate sentence in context or following additional neutral discourse. We measured accuracy, probe recognition time, and reading times of the probe sentences. Results showed that, at the immediate time point, participants correctly accepted the identical probes with high accuracy and short recognition times, but that this effect reversed to chance-level accuracy and significantly longer recognition times at the delayed time point. We also found that participants falsely accept the enriched probe at both time points 50% of the time. There were no reading-time differences between identical and enriched probes, suggesting that enrichment might not be an early, mandatory process for indeterminate sentences. Overall, results suggest that while context produces an enriched proposition, anunenriched proposition true to the indeterminate sentence also lingers in memory.
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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 | 0.003 | 0.032 |
| 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 | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".