Bibliographic record
Abstract
Cultures of sharing and collaboration are essential to supporting instruction practices, yet there is limited literature on how these cultures are successfully cultivated in libraries. In this paper, I explore cultures of sharing and collaboration among instruction librarians in Canadian academic libraries. I report on a series of semi-structured interviews (n=14) I conducted with librarians who support or provide information literacy at their institutions. The interview data was reviewed using a thematic analysis approach (Braun and Clark 2022) and coded in NVivo. I explore the barriers and supports to sharing and collaboration as documented in the interviews. Barriers include a) instructional silos caused by the liaison model; (b) a lack of trust in sharing one’s teaching with colleagues; (c) the lack of prioritizing instruction in institutions; and (d) limited time to engage in collaborative work. The supports for sharing and collaboration include (a) intentionally building personal relationships, (b) developing a structure for sharing, and (c) having dedicated time for collaborative work. Based on these findings, practical ways sharing and collaboration can be cultivated in libraries will be explored.
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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 | 0.008 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.013 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.025 | 0.012 |
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".