Evaluation of the Career Development and Compensation Program in the Department of Paediatrics at The Hospital for Sick Children
Bibliographic record
Abstract
The Career Development and Compensation Program (CDCP) was created by the Department of Paediatrics at The Hospital for Sick Children, in Toronto, Ontario, to provide clearly defined job expectations, enhance career development and assess performance through two distinct processes: the annual review and the triennial review. Staff are expected to advance the goals of the department and the hospital through activities in clinical care, education and mentorship, and research and are rewarded for excellence through compensation and career advancement. We evaluated the CDCP and conducted interviews with 27 members of the department; these formed the primary basis for our summative evaluation. The study objectives were to evaluate (1) mechanisms to recognize contributions, (2) processes used to ensure staff accountability and (3) opportunities to increase efficiencies. Interviews with members of the department resulted in a broad and comprehensive understanding of the CDCP. It is regarded as a rigorous, transparent and fair program. Concerns about the CDCP stem from the potential negative outcomes of assigning value to particular activities, the inequitable level of support provided to staff across the department and the costs of the review processes. Several recommendations were identified that serve to increase equality and strengthen supports for members of the department, to improve the ability of the CDCP to evaluate the softer aspects of clinical care and scholarship and to adopt a more holistic and integrated approach in the evaluation of staff. These re-formed arrangements build upon past modifications to the CDCP and represent natural progressions in the development of a program that has wide support from members of the department.
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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 | 0.129 | 0.127 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".