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Record W4367159328 · doi:10.7202/1078110ar

Governmental Indian Policy, Administration, and Economic Planning in the Eastern Subarctic

2021· article· en· W4367159328 on OpenAlexaffabout
Edward J. Hedican

Bibliographic record

VenueCulture · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsAdministration (probate law)Agency (philosophy)Position (finance)Human settlementDiversity (politics)Subarctic climatePublic administrationControl (management)Government (linguistics)Political scienceBusinessGeographyEconomicsFinanceSociologyManagementLaw

Abstract

fetched live from OpenAlex

This paper undertakes a comparative analysis of the effects of governmental administration and planning in northern Native communities. The effects are examined with reference to two community types — reserves, with their single-stranded ties to Ottawa’s Department of Indian Affairs, and non-reserve settlements, which have a diversity of outside contacts. It is argued that the limited external contacts characteristic of reserves impede local initiative and foster reliance on decisions made by Government personnel. By contrast, the non-reserve community is able to exercise greater local control because no single external agency is in a position to dominate local affairs. Lacking significant outside structures, leadership in the non-reserve community is able to pursue more autonomous and coherent local planning for economic change.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.819
Threshold uncertainty score0.360

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0040.006
Scholarly communication0.0040.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.320
Teacher spread0.304 · 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 designObservational
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

Citations2
Published2021
Admission routes2
Has abstractyes

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