So <i>that's</i> why I don't remember: Normalising forgetting of childhood events influences false autobiographical beliefs but not memories
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We investigated changes in autobiographical belief and memory ratings for childhood events, after informing individuals that forgetting childhood events is common. Participants received false prevalence information (indicating that a particular childhood event occurred frequently in the population) plus a rationale normalizing the forgetting of childhood events; false prevalence information alone; or no manipulation, for one (Study 1) or two (Study 2) unlikely childhood events. Results demonstrated that combining prevalence information and the "forgetting rationale" substantially influenced autobiographical belief ratings, whereas prevalence information alone had no impact (Study 1) or a significantly lesser impact (Study 2) on belief ratings. Prevalence information consistently impacted plausibility ratings. No changes in memory ratings were observed. These results provide further support for a nested relationship between judgements of plausibility, belief, and memory in evaluating the occurrence of autobiographical events. Furthermore, the results suggest that some purported false memory phenomena may instead reflect the development of autobiographical false beliefs in the absence of memory.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it