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Record W2201686726

Evaluating Military Balances Through the Lens of Net Assessment: History and Application

2010· article· en· W2201686726 on OpenAlexvenueno aff
Thomas Skypek

Bibliographic record

VenueJournal of military and strategic studies · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicMilitary History and Strategy
Canadian institutionsnot available
Fundersnot available
KeywordsBlueprintPentagonPolitical scienceThreat assessmentMultidisciplinary approachCold warTask (project management)ManagementPublic administrationLawEngineeringEconomics
DOInot available

Abstract

fetched live from OpenAlex

For senior statesmen and their advisers, the task of evaluating external security threats and identifying strategic opportunities is a perennial challenge. This article examines one contemporary approach the United States Department of Defense has employed to understand the complex state-based military and security threats confronting the United States: net assessment. Net assessment is a multidisciplinary framework that is comparative, diagnostic, and forward-looking. This article fills an important gap in the scholarly literature by using declassified primary sources to trace the history and development of net assessment within the United States Department of Defense during the cold war. The author attempts four major tasks in this article: first, to provide a clear definition of net assessment, as practiced by the Pentagon’s Office of Net Assessment; second, to present a blueprint for the conduct of net assessments; third, to detail its history in the Department of Defense during the cold war; and fourth, to explain its value as an analytical framework for analysts and policymakers. It provides a blueprint for thinking about strategic military competitions through the lens of net assessment.

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)0.002
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.218
Threshold uncertainty score0.611

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
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 head0.109
GPT teacher head0.387
Teacher spread0.278 · 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 designTheoretical or conceptual
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

Citations4
Published2010
Admission routes1
Has abstractyes

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