The Impact of Rape Myth Education on Jury Decision-Making: A Systematic Review
Bibliographic record
Abstract
A systematic review of research exploring the impact of providing rape myth countering information to mock-jurors was conducted. The primary aim of the review was to inform the development of an educational intervention for jurors to reduce potential bias in their decision-making based on belief in prevalent rape myths. In total, the following 12 databases were searched: British Education Index, CINAHL, Child Development and Adolescent Studies, Criminal Justice Abstracts, Educational Administration Abstracts, ERIC, MEDLINE, PsycArticles, PsycInfo, PubMed, Scopus, and Social Care Online. The databases were filtered to return peer-reviewed publications, written in English, and published between 1980 and 2023. The search returned 6,119 potential articles. After duplicates were removed, the 3,202 remaining publications were screened. Only studies that presented rape myth countering information to participants within a mock-juror paradigm were included. Studies that did not compare an information condition to a no-information control condition were excluded, as were those which concerned male rape myths, given the focus on female rape myth beliefs in this review. Eight studies were reviewed and were critically appraised according to validity criteria utilized by Dinos et al. Some evidence emerged to suggest that the provision of judicial directions, expert witness testimony, and complainant statements regarding rape myths can impact upon jury decision-making although the findings were mixed overall. Study limitations regarding internal and external validity were frequently present. Recommendations regarding future research questions and methods are advanced, including those that can inform the development of an effective intervention for jurors.
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.
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 | 0.027 | 0.124 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".