MétaCan
Menu
Back to cohort
Record W3084500699 · doi:10.22215/etd/2020-14037

One Horse Race? A study of interoperability in Canada's Future Fighter Capability Project

2020· dissertation· en· W3084500699 on OpenAlexaffabout
William Richardson

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEconomics, Econometrics and Finance
TopicDefense, Military, and Policy Studies
Canadian institutionsCarleton UniversityDepartment of National Defence
Fundersnot available
KeywordsInteroperabilityGovernment (linguistics)EngineeringKey (lock)Selection (genetic algorithm)Process (computing)Public administrationBusinessComputer securityEngineering managementPolitical scienceComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Through the $19 billion Future Fighter Capability Project, the Government of Canada will procure a replacement for the CF-18. However, the requirement that the future fighter be "seamlessly interoperable" with key allies calls into question whether the competitive selection process can be run in good faith. [National Defence, 2018] This study argues that contemporary Canadian defence policy is oriented around partnerships with other states, especially the US, and that interoperability would therefore best be attained through the selection of a fifth-generation American platform. However, it is unclear that the FFCP evaluation criteria, which include mandatory and rated technical requirements as well as pillars for cost and industrial offsets, account for high-end tactical networking and new allied technical standards. The FFCP may result in the acquisition of a type that prevents the CAF from interoperating "seamlessly" with allies over its lifecycle. This risk undermines Canada's reliance on partnerships for national defence.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.082
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.039
GPT teacher head0.248
Teacher spread0.209 · 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.

Study designObservational
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
Published2020
Admission routes2
Has abstractyes

Explore more

Same topicDefense, Military, and Policy StudiesFrench-language works237,207