"Thank You Very Much... You Can Leave Our Community Now.”: Geographies of Responsibility, Relational Ethics, Acts of Refusal, and the Conflicting Requirements of Academic Localities in Indigenous Research
Bibliographic record
Abstract
This paper reports on the findings from a series of twenty in-depth, semi-structured interviews that explored how a group of leading Canadian health researchers who are recognized for their excellence in community-engaged Indigenous health research envision enacting an anti-colonial research agenda and the inherent tensions of doing so in institutional settings. Interview transcripts were thematically analyzed in order to explore how the different places that shape community-engaged scholarship (Community spaces, Offices of Research Ethics, and Office of Finance and Administration) 1) produce different, often conflicting understandings of responsibility; 2) how different spaces constrain and shape agency in terms of enacting forms of responsibility in research, and; 3) the role that settler subjectivities have in shaping acts of interpretation that are productive of institutionally mediated forms of responsibility. We organize themes of responsibility, relational ethics, and acts of refusal around the locales through which they are produced and mediated in order to display narratives relating to each site. Specifically, we highlight how relationally negotiated formulations of ethical responsibility, which occur between Indigenous community partners and researchers, can be circumscribed or marginalized by existing institutional structures. By making visible the ways in which conflicting responsibilities emerge and must be negotiated in working toward anti-colonial research relationships, our findings contribute to ongoing conversations regarding Indigenous-settler alliances in health research.
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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 | 0.029 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.043 | 0.115 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.003 | 0.005 |
| 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".