The How and the Why: An Argument for a Theory-Oriented Approach to LIS Administration and Management Scholarship and Practice
Bibliographic record
Abstract
"Management" and "leadership" are currently two buzz words in the Canadian LIS community. Although these topics receive scholarly attention, epistemological and theoretical basis for that work is limited. LIS needs to expand the conceptual frameworks used to study these topics by looking to the discipline of Educational Administration and Leadership.La gestion et le leadership sont des mots à la mode au sein de la communauté canadienne des sciences de l'information. Malgré toute l'attention que leur accorde la recherche universitaire, les bases épistémologiques et théoriques pour en parler sont limitées. La communauté des sciences de l'information doit élargir le cadre conceptuel d'étude de ces sujets en se basant sur l'administration et le leadership en milieu scolaire.
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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 | 0.040 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.017 | 0.124 |
| Scholarly communication | 0.025 | 0.032 |
| Open science | 0.006 | 0.010 |
| Research integrity | 0.012 | 0.017 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".