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Record W2164750281 · doi:10.1177/0095327x07312087

Sociology in the Canadian Military Academy Curriculum

2008· article· en· W2164750281 on OpenAlexaboutno aff
Franklin C. Pinch, Éric Ouellet

Bibliographic record

VenueArmed Forces & Society · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Security, and Conflict
Canadian institutionsnot available
Fundersnot available
KeywordsHegemonyCurriculumSociologyContext (archaeology)Multidisciplinary approachEngineering ethicsMilitary sociologyMilitary scienceMilitary personnelSocial sciencePublic relationsPolitical scienceLawPedagogyEngineeringPoliticsMilitary operations other than war

Abstract

fetched live from OpenAlex

Despite its content being perceived as highly relevant to Canadian Forces (CF) leader development and current and future role demands, sociology has not become permanently embedded in the Canadian military college (milcol) curriculum. We argue that among other factors, this has been the result of such influences as lack of interest and/or support from academic sociologists outside the military; hegemony of other disciplines within the military; reaction of the military system to sociological topics and results; the number and organization of uniformed and civilian sociologists internally; and the failure of military sociologists to adequately market themselves or to follow up on the gains they have made. Notwithstanding, the authors note that recent developments both outside and inside the military college environment offer some promise of improved prospects for sociology (and anthropology): preferably, within a more multidisciplinary instructional context.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.965
Threshold uncertainty score0.672

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0130.005
Scholarly communication0.0050.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0300.002

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 head0.042
GPT teacher head0.307
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 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

Citations2
Published2008
Admission routes1
Has abstractyes

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