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Record W4231491941 · doi:10.24124/2010/bpgub680

Breaking copper: Legislating the repatriation of First Nations cultural property to restore self-determination and promote reconciliation.

2010· dissertation· en· W4231491941 on OpenAlexaboutno aff
Pamela Flagel

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsnot available
Fundersnot available
KeywordsRepatriationCultural propertyLegislationTreatyPolitical scienceCultural heritageNegotiationGovernment (linguistics)LegislatureLawLaw and economicsSociology

Abstract

fetched live from OpenAlex

The repatriation of cultural property to First Nations is often guided by voluntary procedures developed by museums, and legislation enacted by government. The treaty process can also direct repatriation negotiations between First Nations and museums. The return of cultural property from museums to First Nations has the potential to restore aboriginal cultural self-determination rights and begin a process of reconciliation between these two groups. However, neither First Nations cultural self-determination nor reconciliation with museums can be achieved through the repatriation of cultural property alone. In order for cultural self-determination to be fully realized complete control over cultural property must be reinstated to First Nations communities. Conditions placed on the care and storage of returned objects can interfere with First Nations cultural practices and can foster mistrust and resentment towards museums. An examination of voluntary policies, treaty processes, and legislative acts demonstrates that legislation is best able to restore full cultural self-determination to First Nations and achieve reconciliation with museums. --P.ii.

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 imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.891
Threshold uncertainty score0.216

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0160.008
Scholarly communication0.0080.006
Open science0.0020.004
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0130.003

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.

Opus teacher head0.061
GPT teacher head0.265
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2010
Admission routes1
Has abstractyes

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