Bibliographic record
Abstract
Purpose This paper aims to explore graduate student experiences of ecohealth communities of practice in Canada, West and Central Africa and Central America, to better understand the role of student knowledge in advancing innovative practices in transdisciplinary, participatory and equitable research approaches. Design/methodology/approach This ethnographic analysis builds on observations of graduate student participants in ecohealth communities of practice activities, along with 26 in-depth interviews conducted in 2011 with graduate students and professionals trained in ecosystem approaches to health. Interviews are transcribed by the author, and coded and analyzed using a grounded theory approach. Findings Although ecohealth communities of practice open new space for students to experiment with innovative practices in transdisciplinary, participatory and equitable research approaches, the surrounding disciplinary, top-down structure of academic and professional careers continue to pose significant obstacles to how students can take up the principles of ecohealth in practice. Through their collective experiences of these obstacles, students have considerable knowledge about the opportunities and constraints that the ecohealth communities of practice afford; however, this student knowledge has not yet been systematized or adequately mobilized. Practical implications Student knowledge gained through shared experiences of ecohealth communities of practice appears to be a critical, necessary and underused component in working on systemic change in the structure of sustainability leadership in higher education. However, more research is needed to understand how greater emphasis could be placed on putting students in charge of confronting the conditions of their own training, to collectively produce alternatives that challenge dominant structural norms. Originality/value The ethnographic approach re-centers student voices within debates about the relevance of ecohealth communities of practice for realizing the aims of transdisciplinary, participatory and equitable research approaches within the context of international sustainability challenges and graduate training.
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.011 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".