Research Ethics in Decolonizing Research With Inuit Communities in Nunavut: The Challenge of Translating Knowledge Into Action
Bibliographic record
Abstract
Research failures are not readily disclosed in research representations. This exclusion is a missed opportunity to practice reflexivity, a practice otherwise crucially important to social science inquiry, and share the learning that was inspired by the failure. In this paper I present and reflect on a research failure that occurred during my doctoral research into alternative, Inuit-centered models of fisheries governance in Nunavut. While working on defining the research, I experienced a far-reaching impasse due to the lack of community response and academic guidance. Eventually, despite the best intentions to engage in decolonizing research, I chose to forgo meaningful community consultation before embarking on my fieldwork. Decolonizing research centers collaboration and local research needs from the outset. At the same time, what it means to negotiate a research relationship is in itself negotiable. Further, the negotiating is often challenged by time constraints, institutional restrictions, and limited financial resources. Lessons learned from my case study include a) that a nonideal start does not mean that the entire research project will fail and b) that participating Indigenous communities have the sovereignty, irrespective of existing protocols, to set the terms under which research can take place. Above all, negotiating a research relationship is about relational work which requires commitment and continuous engagement.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Science and technology studies Domain: not available · Genre: Empirical About the Canadian research system: yes · About a Canadian topic: yes | Qualitative | high |
| gpt | MetaresearchResearch integrity Domain: Methods · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Qualitative | high |
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 | 0.251 | 0.136 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.050 | 0.120 |
| Scholarly communication | 0.022 | 0.012 |
| Open science | 0.007 | 0.019 |
| Research integrity | 0.008 | 0.013 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".