Serial position functions in general knowledge.
Bibliographic record
Abstract
Serial position functions with marked primacy and recency effects are ubiquitous in episodic memory tasks. The demonstrations reported here explored whether bow-shaped serial position functions would be observed when people ordered exemplars from various categories along a specified dimension. The categories and dimensions were: actors and age; animals and weight; basketball players and height; countries and area; and planets and diameter. In all cases, a serial position function was observed: People were more accurate to order the youngest and oldest actors, the lightest and heaviest animals, the shortest and tallest basketball players, the smallest and largest countries, and the smallest and largest planets, relative to intermediate items. The results support an explanation of serial position functions based on relative distinctiveness, which predicts that serial position functions will be observed whenever a set of items can be sensibly ordered along a particular dimension. The serial position function arises because the first and last items enjoy a benefit of having no competitors on 1 side and therefore have enhanced distinctiveness relative to mid-dimension items, which suffer by having many competitors on both sides.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".