Engaged acclimatization: Towards responsible community‐based participatory research in Nunavut
Bibliographic record
Abstract
In this article, we consider the formation of responsible research relationships with Inuit communities from an “outsider” researcher perspective. Cautious not to prescribe what counts as responsible, we draw on research experiences in several Nunavut communities to introduce and explain “engaged acclimatization.” This neologism refers to embodied and relational methodological processes for fostering responsible research partnerships, and is inspired by the significance of preliminary fieldwork in orienting the lead author's doctoral thesis. As a complement to community‐based participatory methodologies, engaged acclimatization facilitates endogenous research by enacting ethics as a lived experience, initiating and nurturing relationships as a central component of research, and centring methods on circumstances within participating communities. After we locate engaged acclimatization within resonant literature and details of interrelated research projects, our article sketches out four aspects of engaged acclimatization: crafting relations, learning, immersion, and activism. In our discussion of each, we integrate specific insights derived from field notes, observations, photographs, critical reflections, and literature that have brought us to this understanding. The four aspects provide conceptual and methodological tools for readers to apply in the contexts of their own research programs or in guidelines for establishing partnerships with Inuit or Aboriginal communities. The value of this article lies in the extent to which it encourages readers to situate engaged acclimatization in their own research and further develop it as a process.
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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 | 0.063 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.036 | 0.055 |
| Scholarly communication | 0.014 | 0.010 |
| Open science | 0.004 | 0.023 |
| 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".