Failing to report details of an event: A review of the directed forgetting procedure and applications to reports of childhood sexual abuse
Bibliographic record
Abstract
Recent reviews of child sexual abuse (CSA) disclosure indicate that many victims delay disclosing abuse for some period of time (e.g., London, Bruck, Ceci, & Shuman, 2005). During this period of non-disclosure, CSA victims may avoid thinking about or discussing their abuse experiences. Some scholars argue that this may lead to a directed forgetting (DF) effect, whereby later recall of the unrehearsed memories becomes more difficult (e.g., M. A. Epstein & Bottoms, 2002). This paper reviews the DF literature and discusses the potential contribution of DF to silence. The review begins with a description of the basic DF protocol used, discusses underlying mechanisms thought to be responsible for the DF effect, and then examines applications of the DF protocol to memory for emotion-laden word lists and autobiographical events. Overall, the applied studies demonstrate that DF effects generalise beyond memory for innocuous word lists; however, we describe several important avenues of research that require further exploration. Most noteworthy, and particularly relevant to the common application of DF to memory for CSA, are those studies that examine the influence of DF on children's autobiographical memory.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".