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Record W7093566125

Les relations donneurs d’ordres sous-traitants dans l’industrie aérospatiale au Québec : une étude exploratoire

2022· other· fr· W7093566125 on OpenAlexaboutno aff

Bibliographic record

VenueCorpus Université Laval (Université Laval) · 2022
Typeother
Languagefr
FieldEconomics, Econometrics and Finance
TopicCinema and Media Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDigital strategyDatabase queryEarly adopter
DOInot available

Abstract

fetched live from OpenAlex

L'industrie aérospatiale mondiale se réorganise pour relever dans les prochaines années les défis d'une croissance considérable. L'importance de cette industrie dans une économie nationale est clairement établie et explique le désir de pays en voie d'industrialisation d'acquérir l'infrastructure nécessaire pour atteindre le marché mondial. Ces nouvelles recrues de l'industrie bouleversent les règles du jeu et forcent les donneurs d'ordres et les sous-traitants à établir des réseaux globaux. Pour ce faire, ils doivent adopter des pratiques reconnues qui leur permettront d'interagir, d'innover et de se développer en partenariat avec des firmes étrangères. Dans cette étude exploratoire nous présentons les résultats d'une enquête sur les relations donneurs d'ordres/sous-traitants dans l'industrie de l'aérospatiale au Québec. Vingt trois entreprises ont été interrogées. L'enquête veut mettre en lumière l'adoption par les entreprises québécoises des meilleures pratiques en ce qui concerne la planification et le contrôle des relations, des transactions et des échanges entre les donneurs d'ordres et les sous-traitants.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.023
Threshold uncertainty score0.166

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.005
Science and technology studies0.0040.001
Scholarly communication0.0040.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.019
GPT teacher head0.181
Teacher spread0.162 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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