Understanding equity and diversity needs among health library professionals in Canada: a survey
Bibliographic record
Abstract
Objective: The Canadian Health Libraries’ Association (CHLA/ABSC) Equity, Diversity and Inclusion (EDI) Task Force conducted an EDI survey in 2023. In addition to gathering information about the demography, education, and employment of health information professionals working in Canadian institutions, the goal of the survey was to assess the support, education and leadership needs of the association in matters relating to diversity and inclusion. Methods: A survey was created based on EDI surveys conducted previously by similar associations, with additional questions relevant to health information professionals in Canada and CHLA/ABSC’s role in matters of EDI. The survey, consisting of 31 questions and employing a variety of formats, was translated into French and administered via SurveyMonkey. It was distributed through email and other channels over the course of two weeks in January 2023. Results: One hundred and sixty-six health information professionals completed the 2023 survey. Most (83%) were CHLA/ABSC members and sixty-three percent were members of CHLA/ABSC chapters. Most were employed in full-time permanent positions (91%) as librarians (67%) or in administration/management positions (16%). Nearly half worked in post-secondary institutions (42%) and half worked in hospital libraries (43%), and most have access to professional development funds from their employers (84%). Most of the respondents do not belong to a visible minority group (86%), do not consider themselves to be of Indigenous ancestry (96%), do not consider themselves to have a disability (72%), and do not identify as 2SLGBTQIA+ (79%). Fifty-nine percent were aged between 35 and 54 years old and sixty-eight percent had less than fifteen years of experience. Slightly over half (54%) reported a salary between $65,000 and $99,999. Respondents indicated that they felt welcome and included (78%) and treated with respect (84%) at CHLA/ABSC events, that there were opportunities within CHLA/ABSC for them to participate at levels they felt comfortable with (82%) and that they felt comfortable sharing their personal perspectives and experiences within CHLA/ABSC (65%). Conclusion: The survey illustrates that CHLA/ABSC consists of a very homogeneous group of professionals. While the majority of members felt welcomed, respected, and were given opportunities to participate in association work and activities, there is definitely room for improvement. Generally, respondents felt that CHLA/ABSC should continue to listen and improve its EDI work by engaging and collaborating with members to deliver current and relevant networking and CE opportunities.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".