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Record W2100485836 · doi:10.1017/s0032247410000124

Resource development and aboriginal culture in the Canadian north

2010· article· en· W2100485836 on OpenAlexaffabout
Angela Angell, John R. Parkins

Bibliographic record

VenuePolar Record · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPoliticsScholarshipSociologyResource (disambiguation)Participatory action researchAcculturationEnvironmental ethicsPolitical scienceGeographySocial scienceAnthropologyEthnic group

Abstract

fetched live from OpenAlex

ABSTRACT This paper examines the relationship between resource development and aboriginal community and cultural impacts in Canada's north from the 1970s to the present. Based on a review of published literature, it is contended that northern centred scholarship can be conceptualised in two phases. These are firstly the community impacts phase (1970 to mid-1990s), a phase guided largely by a cultural politics of assimilation, a sociology of disturbance, and an anthropology of acculturation; and secondly the community continuity phase (mid-1990s to present), a phase underpinned by political empowerment, participatory social impact assessment, and the influence of cultural ecology. Due to these shifting political dynamics and research frameworks, and a lack of longitudinal research in the north over the last four decades, it is concluded that the nature of the relationship between resource development and aboriginal culture remains elusive and subject to wide ranging interpretation. Analysis shows that cultural impacts from resource development are dependent on the scale of development and spatial disturbance. It also shows growing political power in the north, a greater focus on community-based research, and renewed discussion of cultural continuity and how it is defined and assessed over time.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.329

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0090.004
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.010
GPT teacher head0.284
Teacher spread0.274 · 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 designQualitative
Domainnot available
GenreEmpirical

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

Citations61
Published2010
Admission routes2
Has abstractyes

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