"In a Good Way": Repatriation, Community and Development in Kitigan Zibi
Bibliographic record
Abstract
In 2005 Kitigan Zibi Anishinabeg successfully repatriated human remains from the Canadian Museum of Civilization. Though repatriation case studies often concentrate on the importance of the material heritage being returned to source communities, the effects of the repatriation process itself can be equally important. This article demonstrates how the repatriation process developed community capacity in Kitigan Zibi and increased unity within the larger Algonquin Nation. The overall process shows the role that repatriation can play in larger questions of Indigenous autonomy, regardless of what material is involved in the claim or whether it is successfully returned to the community. Resume: En 2005, la communaute Anishinabeg de Kitigan Zibi a rapatrie des restes humains du Musee canadien des civilisations. Si la plupart des etudes de cas sur le rapatriement misent sur l’importance du retour du patrimoine materiel a la communaute d’origine, le processus de rapatriement lui-meme peut aussi avoir des repercussions importantes sur la communaute. Cet article explique l’impact que le rapatriement a eu sur le developpement de ressources communautaires a Kitigan Zibi, ainsi que le role qu’il a joue dans la creation d’un sentiment de solidarite au sein de la Nation algonquine. Le processus de rapatriement s’inscrit ainsi comme un aspect non negligeable de la question plus large de l’autonomie culturelle autochtone, et ce, peu importe le patrimoine materiel qui fait l’objet de la demande ou meme le resultat cette demande.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.011 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".