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Record W4319165437 · doi:10.1093/polsoc/puad001

The politics of military megaprojects: discursive struggles in Canadian and Australian naval shipbuilding strategies

2023· article· en· W4319165437 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePolicy and Society · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicPublic Procurement and Policy
Canadian institutionsSimon Fraser UniversityToronto Metropolitan University
Fundersnot available
KeywordsMegaprojectProcurementShipbuildingPoliticsScale (ratio)BusinessCredibilityIndustrial organizationPolitical scienceEconomicsManagementMarketing

Abstract

fetched live from OpenAlex

Abstract Large-scale military platform procurement is an essential but understudied component of the policy studies of megaprojects. Procurement decisions in this area, from ships to aircraft, are examples of a specific type of often very expensive purchases which feature complex multi-actor and multiyear processes characterized by high degrees of conflict between actors over purchases and planning horizons. This study of military procurement efforts of this type demonstrates the importance of maintaining policy ‘alignment’ between governments and service providers for successful megaproject procurement to occur and suggests several strategies for accomplishing this that can be applied to similar large-scale but nondefense-related projects, ranging from hydroelectric dams to high-speed railway development.

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.

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)0.000
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 score0.692
Threshold uncertainty score0.832

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.025
GPT teacher head0.284
Teacher spread0.259 · 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