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Record W3046844505

The influence of local institutional and historical frameworks on a globalized industry: The case of the pharmaceutical industry in France and Quebec

2020· preprint· en· W3046844505 on OpenAlexaboutno aff
Maé Geymond

Bibliographic record

VenueRePEc: Research Papers in Economics · 2020
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicFirm Innovation and Growth
Canadian institutionsnot available
Fundersnot available
KeywordsCapitalismGlobal value chainValue (mathematics)Economic geographyPharmaceutical industryGlobalizationBusinessIndustrial organizationEconomic systemEconomyMarket economyEconomicsPolitical scienceLaw
DOInot available

Abstract

fetched live from OpenAlex

In this paper, we combine the Varieties of Capitalism and the global value chain approaches, considering the interaction between lead firms' global strategies and national capitalism, to show how local pharmaceutical employment results from this interaction. Our analysis is grounded in the comparison between France and Quebec. The first part presents the relevant differences in both historical and institutional elements. Second, after highlighting the similarities that can be attributed to global dynamics, we detail the mechanisms by which local institutions shape the global value chain implantation, giving different forms to the employment structure and dynamcis. We show that France is clearly oriented towards manufacturing activity because of industrial history and market features, whereas Quebec has a commercial specialty and an outsourced R&D as a result of high prices and the global organization of research

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.965
Threshold uncertainty score0.251

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0050.006
Scholarly communication0.0070.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.055
GPT teacher head0.319
Teacher spread0.264 · 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 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

Citations1
Published2020
Admission routes1
Has abstractyes

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Same venueRePEc: Research Papers in EconomicsSame topicFirm Innovation and GrowthFrench-language works237,207