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Record W3083742224 · doi:10.1017/s1557466018014377

Tightly Bound: The United States and Australia's Alliance-Dependent Militarization

2018· article· en· W3083742224 on OpenAlexaboutno aff
Richard Tanter

Bibliographic record

VenueJapan focus · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicMilitary and Defense Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMilitarizationAlliancePolitical scienceEconomic geographyGeographyPoliticsLaw

Abstract

fetched live from OpenAlex

Contemporary Australia is a case of dependent, high-technology liberal militarization, but with distinctive characteristics pointing to a model that must look beyond standard concerns with increasing national defense budgets, more and better weapons systems, an “exceptionalist” approach to immigration security and a predilection for use of military force in international affairs. In a world and time where militarization is a global norm embedded in globe-spanning military alliances and world-wide networks of foreign military bases, discerning the lineaments of one particular national instance can be both difficult and potentially misleading. In liberal democracies, national self-conceptions resist identification with the harsh implications of reliance on, or valorization of, military force, unless it can be viably represented as defense of freedom, just war, or wars against unspeakable Others. And in the case of liberal democracies originating in a settler state with ongoing unrecognized conquest of indigenous peoples – think Australia, the United States, Canada and Israel – the racially inflected violence at the foundations of state-formation and national identity continues to ramify through the default settings of contemporary foreign policy. All three qualities distinguish the contemporary pattern of Australian militarization from the standard versions of either exceptionalist or liberal militarization.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.126
Threshold uncertainty score0.250

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.010
Scholarly communication0.0040.003
Open science0.0000.006
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.035
GPT teacher head0.309
Teacher spread0.274 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2018
Admission routes1
Has abstractyes

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