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Record W2926006916

A Mixed Methods Study of Enlistment of Indigenous Men on Reserves in the First World War

2018· article· en· W2926006916 on OpenAlexaffvenueabout
Katharine McGowan, Simon Palamar

Bibliographic record

VenueJournal of military and strategic studies · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicMilitary History and Strategy
Canadian institutionsUniversity of CalgaryMount Royal University
Fundersnot available
KeywordsIndigenousBureaucracyGovernment (linguistics)Independence (probability theory)Context (archaeology)CovertMemoirPower (physics)TreatyPolitical scienceRhetoricSociologyLawPolitical economyPublic administrationPoliticsGeography
DOInot available

Abstract

fetched live from OpenAlex

The First World War triggered opposite reactions from Indigenous men and the Canadian government; the former sought a combination (varying by personal degrees) of independence, cultural expression, treaty obligations and choice, while the latter saw an opportunity to strengthen their control of Indigenous communities for assimilative ends. We know about the experiences of Indigenous soldiers through letters home, the post war production of cultural artifacts and the too-rare memoir, but accessing the extent of the government's attempts at control within this context, specifically the highly personal and often fraught choice to enlist, requires striping away government rhetoric and bureaucratic bluff. In this research note, we assess patterns of recruitment to isolate the specific effect of the government decision to deliberately overlap Indian Affairs and military authority figures in the form of Agents-recruiters. This cliometric analysis highlights the power of this combination of expedient government interest at the expense of Indigenous community integrity.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.064
Threshold uncertainty score0.956

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.133
GPT teacher head0.398
Teacher spread0.265 · 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 teacher head, 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

Citations0
Published2018
Admission routes3
Has abstractyes

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