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Record W3026110009 · doi:10.1177/0022526620920789

Government procurement policy and the establishment of manufacturing: Aircraft industry in Australia, Canada and South Africa 1918–39

2020· article· en· W3026110009 on OpenAlexaboutno aff
Malcolm Abbott, Jill Bamforth

Bibliographic record

VenueThe Journal of Transport History · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicDefense, Military, and Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsProcurementGovernment (linguistics)Investment (military)Government procurementStrengths and weaknessesWorld War IIFormative assessmentAircraft industryManufacturingEconomyBusinessPolitical scienceEngineeringEconomicsAeronauticsPoliticsLawMarketingSociology

Abstract

fetched live from OpenAlex

The purpose of this paper is to compare and contrast the different aircraft procurement policies of the Canadian, Australian and South Africa air forces in the formative years of the industry in each country between the world wars. In doing so, it will highlight some of the strengths and weaknesses exhibited by the different approaches taken by the three governments attempting to build up aircraft manufacturing in the inter-war period (1918–39). Before 1938, the Australian and South African governments made no attempt to attract investment by British and American aircraft manufacturers, the opposite of what Canadian Government did; as a result, the industry was less developed in the former two countries when the Second World War broke out.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score0.586

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0050.002
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.002
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 head0.044
GPT teacher head0.202
Teacher spread0.158 · 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 designNot applicable
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

Citations3
Published2020
Admission routes1
Has abstractyes

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