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Record W3167121930 · doi:10.3917/riges.462.0012

Commerce de détail : une pandémie accélératrice de changements

2021· article· fr· W3167121930 on OpenAlexaffvenueabout
Jean-Guy Côté

Bibliographic record

VenueGestion · 2021
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicConsumer Retail Behavior Studies
Canadian institutionsRéseau Technoscience
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

En mars 2020, quand la pandemie de COVID-19 nous a pour ainsi dire assignes a residence, les rangees et les vitrines des detaillants se sont videes. Si, comme commercant, vous aviez la malchance de vendre des produits non essentiels, votre magasin (s’il etait ouvert) ne recevait la visite d’aucun client. Mais votre site transactionnel, lui, roulait a fond. Les contraintes auxquelles certaines regions sont toujours soumises a l’heure actuelle ont cree un choc dans le secteur du commerce de detail, qui emploie plus de 400 000 personnes au Quebec.Alternate abstract:In March 2020, when the COVID-19 pandemic put us under house arrest, the rows and storefronts of retailers emptied. If, as a merchant, you were unlucky to sell non-essential products, your store (if it was open) was not visited by any customers. But your transactional site was running at full speed. The constraints that some regions are still subject to today have created a shock in the retail sector, which employs more than 400,000 people in Quebec.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.470
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.001

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 head0.043
GPT teacher head0.275
Teacher spread0.233 · 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
Published2021
Admission routes3
Has abstractyes

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