Alliance members’ roles in collective field-building: an assessment of leadership and championship within the Population Health Intervention Research Initiative for Canada
Bibliographic record
Abstract
Abstract Background The Population Health Intervention Research Initiative for Canada (PHIRIC) is a multi-stakeholder alliance founded in 2006 to advance population health intervention research (PHIR). PHIRIC aimed to strengthen Canada’s capacity to conduct and use such research to inform policy and practice to improve the public’s health by building PHIR as a field of research. In 2014, an evaluative study of PHIRIC at organisational and system levels was conducted, guided by a field-building and collaborative action perspective. Methods The study involved 17 qualitative key informant interviews with 21 current and former PHIRIC Planning Committee and Working Group members. The interviews examined how individuals and organisations were acting as champions and exerting leadership in building the field of PHIR. Results Founding PHIRIC organisational members have been championing PHIR at organisational and system levels. While the PHIR field has progressed in terms of enhanced funding, legitimacy, profile and capacity, some members and organisations faced constraints and challenges acting as leaders and champions in their respective environments. Expectations about the future of PHIRIC and field-building of PHIR were mixed, where longer-term and founding members of PHIRIC expressed more optimism than recent members. All agreed on the need for incorporating perspectives of decision-makers into PHIR directions and initiatives. Conclusions The findings contribute to understanding alliance members’ roles in leadership and championship for field-building more generally, and for population health and PHIR specifically. Building this field requires multi-level efforts, collaborative action and distributed leadership to create the necessary conditions for PHIRIC members to both benefit from and contribute to advancing PHIR as a field. Lessons from this 'made in Canada' model may be of interest to other countries regarding the structures needed for PHIR field-building.
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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 | 0.100 | 0.093 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.033 | 0.013 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.006 | 0.023 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".