Perceptions of laboratory animal facility managers regarding institutional transparency
Bibliographic record
Abstract
Institutions that conduct animal research are often obliged to release some information under various legal or regulatory frameworks. However, within an institution, perspectives on sharing information with the broader public are not well documented. Inside animal facilities, managers exist at the interface between the people who conduct animal research and those charged with providing care for those animals. Their perception of transparency may influence their interpretation of the institutional culture of transparency and may also influence others who use these facilities. The objective of our study was to describe perceptions of transparency among animal research facility managers (all working within the same ethical oversight program), and how these perceptions influenced their experiences. Semi-structured, open-ended interviews were used to describe perceptions and experiences of 12 facility managers relating to animal research transparency. Four themes emerged from the participant interviews: 1) communication strategies, 2) impact on participant, 3) expectations of transparency, and 4) institutional policies. Similarities and differences regarding perceptions of transparency existed among participants, with notable differences between participants working at university versus hospital campuses. These results illustrate differences in perceptions of transparency within one institutional animal care and use program. We conclude that institutions, regulators and the public should not assume a uniform interpretation of a culture of transparency among managers, and that sustained communication efforts are required to support managers and to allow them to develop shared perspectives.
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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 | 0.031 | 0.060 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".