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Record W4308202825 · doi:10.18357/tar131202220756

FM 3-24 and Religious Literacy in American Military Operations in the Middle East

2022· article· en· W4308202825 on OpenAlexaffvenue
Samantha M. Olson

Bibliographic record

VenueThe Arbutus Review · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical and Linguistic Studies
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsFunctional illiteracyMiddle EastPolitical scienceLiteracyForeign policySociologyPolitical economyLawPolitics

Abstract

fetched live from OpenAlex

In August 2021, the Taliban’s success in Afghanistan shocked American citizens and foreign policy analysts. Many counterinsurgency experts sought to explain this phenomenon by focusing on tactical and strategic military failures; however, such explanations often neglected to investigate the religious literacy of American troops engaged in counterinsurgency operations in the Middle East. By considering the treatment of religious literacy in General David Petraeus’s landmark field manual, FM 3-24, a startling degree of religious illiteracy is revealed within counterinsurgency operational protocols. While a historically and culturally focused “civilizational approach” is often proposed by foreign policy analysts as a potential solution to the problem of religious illiteracy in counterinsurgency operations, this approach also falls short of addressing the complex realities that confront American “liberators,” whom locals often perceive to be foreign invaders. This article therefore addresses the disconnect between American military strategy, foreign policy, and the tactical realities encountered by military personnel stationed in the Middle East. Resultantly, this article argues that improved mandatory religious literacy training for American troops is critical not only for conducting successful operations in the Middle East but also for ending, rather than reinvigorating, conflicts abroad.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.950
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.059
GPT teacher head0.330
Teacher spread0.271 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2022
Admission routes2
Has abstractyes

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