Creating space for negotiating the nature and outcomes of collaborative research projects with Aboriginal communities
Bibliographic record
Abstract
This article investigates intellectual property and ethical issues involved in negotiating research processes and outcomes in collaborative projects with Aboriginal communities. A series of ideas are outlined to lay a foundation for thinking about ways to create a conceptual space for open and constructive discussions between research partners. Habermas’s notion of “communicative space” is applied to a partnership between southern-based anthropologists and members of the Inuvialuit community of the Canadian Western Arctic. This partnership is focused on documenting knowledge about a large and comprehensive collection of ancestral ethnographic objects housed at the Smithsonian Institution in Washington, D.C., and on disseminating this knowledge in meaningful ways to the Inuvialuit, anthropological, and museum communities. This article presents a suite of methods generated by the research group that lay some useful parameters for designing research and fostering trust and investment among partners. It also discusses the dynamics of community-based research practices and, specifically, methods for conceiving, constructing, and sustaining research projects.
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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 | 0.216 | 0.162 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.033 | 0.072 |
| Scholarly communication | 0.030 | 0.027 |
| Open science | 0.005 | 0.040 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".