Representing Complex Narrative Goal Structures: Competing Memory-Based and Situational Influences
Bibliographic record
Abstract
This study assessed the relative contribution of situational and memory-based influences to the reader's monitoring of complex narrative goal structures. In 2 experiments, people read stories according to which 2 collaborative subgoals had to succeed for a main goal to be achieved. At a story target region describing an attempt on the main goal, the reader had to make a recognition decision about a probe word representing a manipulated subgoal. Experiment 1 varied subgoal success, presence or absence of overlap between the target and the manipulated-subgoal region, and quality of overlap (either "neutral" or involving a story contradiction). Immediately after Target Sentence 2, probe recognition times favored the influence of situational representations over superficial overlap. Experiment 2 revealed that superficial overlap did not contribute to the results of the contradiction-overlap condition of Experiment 1. We propose that these results reflect the interplay of situational and memory-based processes rather than the predominance of 1 or the other.
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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 | 0.002 | 0.025 |
| 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 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".