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Record W1993489224 · doi:10.1080/01402390.2011.561078

Institutional Analysis and Irregular Warfare: A Case Study of the French Army in Algeria 1954–1960

2011· article· en· W1993489224 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Strategic Studies · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicCommunism, Protests, Social Movements
Canadian institutionsRoyal Military College of Canada
FundersDefence Research and Development Canada
KeywordsNormativeAdaptation (eye)Political scienceInstitutional analysisInstitutional changeKey (lock)SociologyLawPublic administrationComputer scienceComputer securitySocial sciencePsychology

Abstract

fetched live from OpenAlex

Abstract This article proposes a case study to illustrate the usefulness of sociological institutional analysis as a method to uncover ‘blue force’ challenges to deal with irregular warfare. The French Army's adaptation to revolutionary warfare in Algeria, starting in 1954, is used to illustrate both the application of the methodology and how institutional forces can hinder as well as overwhelm transformation for irregular warfare. The analysis emphasizes three key dimensions of the French Army's institutional adaptation: the regulative, normative and cognitive. These empirical elements are used to show how they interacted and influenced the institutional implementation of the French COIN structures.

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.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.123
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.196
GPT teacher head0.373
Teacher spread0.177 · 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