Perspectives on the academic mission in Quebec’s health and social services system: a qualitative study
Bibliographic record
Abstract
Purpose Academic health centers play a central role in integrating research, education and specialized care within health systems. In Quebec (Canada), these centers operate within a unique designation process that defines their academic mission and functions. This project, supported by the Ministry of Health and Social Services, explores how the academic mission is perceived and defined by those involved in its implementation, highlighting key functions, challenges and opportunities for its evolution. Design/methodology/approach A qualitative case study was conducted in 2021, involving 43 group interviews with 322 participants from designated and non-designated health and social services centers, universities, public-sector health organizations and national institutes. Data were analyzed using content analysis, combining deductive and inductive approaches to identify key themes. Findings The academic mission remains focused on supporting care and services to improve population health and well-being. Interviewees emphasized the need to create value from academic mission activities and strongly believe in their positive impact. However, they also identified multiple barriers, including lack of recognition, limited resources and integration challenges. While research and education functions were clearly defined, other functions – such as knowledge translation, diffusion, health intervention and technology assessment and leading practices – were more difficult to define due to uncertainties regarding their objectives, implementation and alignment within the academic mission. Originality/value This study provides empirical insights into the evolving academic mission within an integrated health and social services system. It offers recommendations for refining and harmonizing the designation process and criteria and strengthening the academic mission’s impact.
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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 | 0.015 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.030 | 0.016 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".