Unequal exchange: western economic logic and Inuit/Qablunaat research relationships
Bibliographic record
Abstract
ABSTRACT For some time, Inuit have made it clear that they wish to play a more substantial role in research with implications for themselves and their territory. To understand how researchers communicate and relate to each other, cultural analysis is often employed. Although cultural differences are relevant to understanding problems in the conduct of research, limiting differences to these realities is overly deterministic and essentialist. Many differences arising in the research process are products of social constructions found in Canadian culture and, increasingly, in Inuit communities. The paper re-examines the complexities of cross-class relations, focusing on how different relations to money, as a proxy for other relations characteristic of the capitalist mode of production, consumption and commodification, impact Inuit interaction with western-educated researchers. Using the Nanisiniq Arviat History Project in the community of Arviat, Nunavut Territory Canada, as a case study, the paper is a qualitative analysis of miscommunication resulting from cross-class differences. The Nanisiniq project was a two-year participatory action research project bringing Inuit youth and elders together to rediscover, interpret and apply knowledge of their history and culture to contemporary social issues affecting them.
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
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 | 0.015 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.032 | 0.043 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".