A mega-analysis of memory reports from eight peer-reviewed false memory implantation studies
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
Understanding that suggestive practices can promote false beliefs and false memories for childhood events is important in many settings (e.g., psychotherapeutic, medical, and legal). The generalisability of findings from memory implantation studies has been questioned due to variability in estimates across studies. Such variability is partly due to false memories having been operationalised differently across studies and to differences in memory induction techniques. We explored ways of defining false memory based on memory science and developed a reliable coding system that we applied to reports from eight published implantation studies (N = 423). Independent raters coded transcripts using seven criteria: accepting the suggestion, elaboration beyond the suggestion, imagery, coherence, emotion, memory statements, and not rejecting the suggestion. Using this scheme, 30.4% of cases were classified as false memories and another 23% were classified as having accepted the event to some degree. When the suggestion included self-relevant information, an imagination procedure, and was not accompanied by a photo depicting the event, the memory formation rate was 46.1%. Our research demonstrates a useful procedure for systematically combining data that are not amenable to meta-analysis, and provides the most valid estimate of false memory formation and associated moderating factors within the implantation literature to date.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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