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Record W2324412691 · doi:10.29173/cjs25677

Garbage In, Garbage Out: Challenges of Model Building in Global History, A Military Historical Perspective

2016· article· en· W2324412691 on OpenAlexvenueno aff
Tonio Andrade

Bibliographic record

VenueThe Canadian Journal of Sociology · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicDefense, Military, and Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsScholarshipPerspective (graphical)SociologyPower (physics)Social sciencePolitical scienceEnvironmental ethicsLawComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

This paper examines two prominent recent attempts to explain the phenomenon of the “rise of the West,” Ian Morris’s model of “Social Development” and Philipp Hoffman’s model of military power (Morris 2010, Morris 2013, Hoffman 2012, Hoffman 2015). Whereas most recent scholarship on the rise of the West has focused on economics, Morris and Hoffman widen the scope of comparison to other areas, in particular focusing on the measurement and explanation of divergences in military effectiveness. By drawing on recent work in China’s military history, the author shows that both models – but particularly that of Morris – are inadequate, falling back on older narratives of Western military superiority that have been challenged or disproven by recent scholarship in global military history. The article suggests, however, that the two models – and especially that of Hoffman – do raise significant new questions for future research, and it concludes by noting that what social scientists need more than new models at present is a closer attention to the rapid and ever increasing proliferation of scholarship in non-Western countries, and in particular that of the Sinophone world.

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)0.000
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.380
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.096
GPT teacher head0.262
Teacher spread0.166 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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