Diversity, equity, and inclusion initiatives for health and medical library workers: A scoping review
Bibliographic record
Abstract
BACKGROUND: Health disparities remain as a systemic challenge. With the emergence of the Black Lives Matter movement and scant evidence of diversity, equity, and inclusion (DEI) initiatives for workers in health science libraries, this scoping review maps evidence that can be incorporated into a culture of change. OBJECTIVES: To identify the extent, type, and location of DEI initiatives being conducted in health science libraries for library workers. METHODS: Eight databases were systematically searched for literature from 2014 onwards, including PubMed, Scopus, and Web of Science. Four reviewers were involved in screening and data extraction. RESULTS: Reviewers excluded 6712 title/abstracts. A total of 177 articles progressed to full-text screening, where 153 were excluded. The final number of articles that underwent data extraction was 24. DISCUSSION: Initiatives primarily occurred in academic libraries, led by library workers. Identities mostly focused on were gender, race, and sexuality, while some initiatives focused on general DEI concepts. Most literature pertained to library patrons, demonstrating a gap in reported initiatives for health science library workers. Assessment of initiatives was lacking, with no validated assessment tools used. All of the articles focused on either the United States or Canada. CONCLUSION: Diversity continues to be a challenge within the profession; this should be mitigated through recruitment and retention strategies along with mentorship for new and diverse librarians.
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How this classification was reachedexpand
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.013 | 0.000 |
| Scholarly communication | 0.001 | 0.021 |
| Open science | 0.000 | 0.008 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".