Citation Impact Factors Among Faculty in Canadian Social Work Programs
Bibliographic record
Abstract
Purpose: We report impact data on faculty ( N = 454) working in 30 of Canada’s accredited social work programs during 2016. Method: Using the Publish or Perish website, faculty member’s h and g indices, and their most frequently cited articles published in the last decade were analyzed both individually and by school. Findings: (a) computed h scores were R a 0.8–11.9, M = 4.4 and g scores were R a 1.3–21.3, M = 7.7; (b) the top-ranked citation impact for programs were the University of Toronto, Dalhousie University, and the University of British Columbia; (c) larger programs had significantly higher citation impact for both h and g scores than smaller programs; (d) 17 (27%) of these authors had 10-year citation counts ranging from 176 to 666; and (e) their topics related to children/youth/adolescents (35%) and health care (35%). Discussion: Based on our work in this area, we offer some constructive recommendations to Canadian social work programs and faculty.
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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 | 0.007 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.038 | 0.058 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".