Sexual Assault Survivors and Information: Needs and Recommendations
Bibliographic record
Abstract
This paper examines the information needs of sexual assault survivors, with a focus on the kinds of information these individuals may be seeking and how libraries can best assist survivors with their information needs. The paper begins with an overview of sexual assault as a pervasive problem in society in order to form a basis of understanding of what a sexual assault survivor may be going through and the kinds of barriers that may affect their information seeking. The information needs of sexual assault survivors are complex because of their experiences of violence and trauma, and these factors often result in mental and physical health challenges, and potentially distressing information seeking experiences. In order to best serve sexual assault survivors in libraries, I recommend a trauma-informed approach to librarianship, which underscores the importance of safety, empathy, and empowerment for the survivor. A trauma-informed approach to librarianship can assist sexual assault survivors in remedying potential distress through forming trust, validating their experiences and identity, valuing their voice, and ultimately, supporting their healing.
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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 | 0.015 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.010 | 0.008 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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".