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Record W2295825416 · doi:10.3138/cbmh.32.2.363

From Milk-Medicine To Public (Re)Education Programs: An Examination Of Anishinabek Mothers’ Responses To Hydroelectric Flooding In The Treaty #3 District, 1900–1975

2015· article· en· W2295825416 on OpenAlexaffvenueabout
Brittany Luby

Bibliographic record

VenueCanadian Journal of Health History · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicSociopolitical Dynamics in Nepal
Canadian institutionsLaurentian University
Fundersnot available
KeywordsHydroelectricitySubsistence agricultureFlooding (psychology)GeographyEconomic shortageEconomic growthSocioeconomicsPolitical scienceGovernment (linguistics)SociologyPsychologyAgricultureEcologyEconomicsArchaeology

Abstract

fetched live from OpenAlex

This paper explores how Anishinabek women managed their households during the hydroelectric boom of the 1950s and provides new insight into flooding impact analyses. To date, historians have sought to understand how hydroelectric development compromised "subsistence" living. Research has addressed declining fish and game populations and the corresponding decline in male employment. But, what do these trends mean once the nets and traps have been emptied? By focusing on the family home, we discover that hydroelectric power generation on the Winnipeg River disrupted the environment's ability to provide resources necessary to maintain women's reproductive health (especially breast milk). Food shortages caused by hydroelectric development in the postwar era compromised Anishinabek women's ability to raise their children in accordance with cultural expectations. What emerges from this analysis is a new lens through which to theorize the voluntary enrolment of Anishinabek children in residential schools in northwestern Ontario.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.996
Threshold uncertainty score0.394

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.002
Scholarly communication0.0010.001
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 head0.115
GPT teacher head0.362
Teacher spread0.247 · 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.

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

Citations15
Published2015
Admission routes3
Has abstractyes

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Same venueCanadian Journal of Health HistorySame topicSociopolitical Dynamics in NepalFrench-language works237,207