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Record W1559826162

"What Makes the Indian Tick?" The Influence of Social Sciences on Canada's Indian Policy, 1947-1964

2001· article· en· W1559826162 on OpenAlexvenueaboutno aff
Hugh Shewell

Bibliographic record

VenueHistoire sociale · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsCollectivismIndividualismKinshipState (computer science)Political scienceSocial scienceSociologyPublic policyModernization theoryPolitical economyPublic administrationLaw
DOInot available

Abstract

fetched live from OpenAlex

The continuing objective of state policy towards First Nations in Canada has been their assimilation into the dominant society. Until World War II the strategy had been to subjugate them through transparently harsh statutory and administrative measures. After the war, a new ostensibly more humane approach to assimilation was introduced. An analysis of archival documents from the Canadian Department of Indian Affairs reveals the role of the social sciences in influencing this approach. Knowledge from the social sciences, applied to Indian policy, reflected the biases of modern liberalism. The social sciences pointed to the required direction of Indian adaptation — the market, individualism, self-reliance, and the family — and to what aspects of Indian culture had to change — collectivism, extended kinship, and gendered roles reflective of traditional rather than modern cultures. Although these state policies enjoyed wide public support, First Nations refused to be mere objects of science and research.

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)0.006
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.279
Threshold uncertainty score0.837

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0350.014
Scholarly communication0.0090.002
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.000

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 head0.012
GPT teacher head0.247
Teacher spread0.234 · 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

Citations8
Published2001
Admission routes2
Has abstractyes

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