A Rapid Review on Complaint Mechanisms for Interpersonal Violence: Integrating Research-Based Recommendations from Multiple Sectors to Inform Sport Settings
Bibliographic record
Abstract
Past studies have highlighted the lack of independent formal complaint mechanisms as one of the most significant barriers to reporting interpersonal violence (IV) in sport. Some countries have since implemented complaint mechanisms specific to sport settings. Evaluations of similar mechanisms in other sectors could inform the development and implementation of complaint mechanisms for IV in sport. This rapid review included studies inside and outside the sport context to document the characteristics of complaint mechanisms of IV, barriers or limitations related to such mechanisms, and recommendations resulting from their evaluation. Following the Cochrane Rapid Reviews Interim Guidance, six databases were searched for peer-reviewed references in English or French, published between 2012 and 2022, and pertaining to the evaluation of formal reporting mechanisms of IV. The 35 references covered mechanisms mainly targeting IV in general (any type) or sexual violence specifically. Complaint mechanisms varied in scope and as a function of their setting, including work, university, military, and medical. We identified barriers and limitations concerning fear of consequences, lack of knowledge, lack of efficiency, lack of trust, and unsupportive culture. Finally, we documented 18 recommendations to improve complaint mechanisms of IV, spanning four categories: (a) organizational accountability, (b) awareness and accessibility, (c) adapted process, and (d) ongoing evaluation. This rapid review draws recommendations from various research disciplines and types of mechanisms to offer a comprehensive portrait of best practices. The findings show that numerous aspects of complaint mechanisms at multiple levels should be considered when developing and implementing complaint mechanisms of IV.
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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 | 0.032 | 0.139 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.029 | 0.022 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".