Bibliographic record
Abstract
Summary Brewin and Andrews (2016) make many cogent observations on the state of knowledge about the development of false autobiographical beliefs and false recollections. Owing to inconsistent use of terminology and imprecise definitions, the framework they propose does not clearly map onto the studies that are summarized, making the resulting estimates of the magnitude of effects across studies unconvincing. A singular focus on the development of ‘full memories’ is not explained, and the key role of autobiographical belief in influencing behavior is underemphasized. Furthermore, the legal applications discussed are not well defined and are limited in scope. Fostering false belief or false imagery for events such as childhood abuse is unacceptable, whether or not suggested events come to be experienced as vivid believed recollections. Copyright © 2016 John Wiley & Sons, Ltd.
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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 | 0.015 | 0.098 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.067 | 0.065 |
| Insufficient payload (model declined to judge) | 0.019 | 0.015 |
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".