Confined to a tokenistic status: Social scientists in leadership roles in a national health research funding agency
Bibliographic record
Abstract
The idea of interdisciplinarity has been taken up by academic and governmental organisations around the world and enacted through science policies, funding programs and higher education institutions. In Canada, interdisciplinarity led to a major transformation in health research funding. In 2000, the federal government closed the Medical Research Council (MRC) and created the Canadian Institutes of Health Research (CIHR). From the outset, CIHR's vision and goals were innovative, as it sought to include the social sciences within its purview alongside more traditional health research sectors. The extent to which it has been successful in this endeavour, however, remains unknown. The aim of our study was to examine how CIHR's intentions to foster inclusiveness and cooperation across disciplines were implemented in the agency's own organisational structure. We focused on social scientists' representation on committees and among decision-makers between 2000 and 2015, one of the key mandates of CIHR being to include the social sciences within its remit and support research in this area. We examined the composition of the Governing Council, the Institute Scientific Directors, the Chairs of the College of Reviewers, and two International Review Panels invited by CIHR. We targeted these committees and decision-makers since they hold the power to influence the field of Canadian health research through the decisions they make. Our findings show that, while CIHR was created with the mandate to support the entire spectrum of health-related research-including the social sciences-this call for inclusiveness has not yet been materialized in the agency's organisational structure. Social scientists, as well as researchers from neighbouring disciplines such as social epidemiology, health promotion and the humanities, are still confined to low levels of representation within CIHR's highest echelons. This imbalance limits social scientists' input into health research in Canada and undermines CIHR's interdisciplinary ambition.
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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 | 0.132 | 0.148 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.055 | 0.059 |
| Scholarly communication | 0.028 | 0.013 |
| Open science | 0.004 | 0.028 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 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".