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Record W2803902134 · doi:10.22215/etd/2015-11074

Pearl Harbor and American Intelligence Culture: Cultural Symbols in American Intelligence Discourse Communities, Meta-Theoretical Lenses and Multi-Perspective Approaches

2015· dissertation· en· W2803902134 on OpenAlexaff
L. Copeland

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicIntelligence, Security, War Strategy
Canadian institutionsCarleton University
Fundersnot available
KeywordsCultural intelligencePerspective (graphical)Symbol (formal)SociologyIntelligence cycleIntelligence analysisHuman intelligenceEpistemologySocial sciencePolitical scienceMilitary intelligencePsychologySocial psychologyArtificial intelligenceLawLinguisticsComputer science

Abstract

fetched live from OpenAlex

Ideas of the world persist long beyond the contexts that gave rise to them. In intelligence, as in strategic culture, these persisting ideas form a culture which shapes the intelligence system. Persisting ideas can come to form part of a national culture that ultimately shapes the actors, interests, and decision-making of intelligence stakeholders. This thesis illuminates how specific American cultural symbols influence and reflect U.S. intelligence ideas, discourses, policies, and practices, thereby contributing to a distinctly "U.S. intelligence culture." As a result, this dissertation demonstrates that national cultural symbols are not epiphenomenal: These symbols tangibly influence the thought and action of diverse audiences both within and outside the formal U.S. intelligence community. Through an analysis of national and institutional definitions, norms, narratives, and warrants, the contours of a uniquely American intelligence culture emerge. A test case of how Pearl Harbor functions as a powerful cultural symbol among intelligence discourse communities illustrates national culture's influence vis--vis policy decisions, intelligence reform, institutional openness, and intelligence education. Ultimately, this dissertation's meta-theoretical lens and multi-perspective approach productively bring together conceptual resources from the fields of Intelligence Studies, Strategic Studies, and International Relations contributing to the development of "intelligence culture" as a theoretically sound and useful approach to studying intelligence-related phenomena.

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 categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.636
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0010.012
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.002
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 head0.143
GPT teacher head0.419
Teacher spread0.276 · 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.

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
Published2015
Admission routes1
Has abstractyes

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