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Record W2051318337 · doi:10.3917/riges.271.0022

Le marketing de partage comme outil de marketing pour l'entreprise

2002· article· fr· W2051318337 on OpenAlexvenueaboutno aff
Normand Turgeon, Delphine Martin

Bibliographic record

VenueGestion · 2002
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Résumé À l’heure de la mondialisation de l’économie, la société civile demande un meilleur partage des ressources disponibles. Le marketing de partage est proposé comme outil pouvant satisfaire à la fois aux impératifs économiques des entreprises et aux demandes de divers groupes œuvrant habituellement en tant qu’organismes sans lut lucratif (OSBL). Cet article décrit ce mode de commercialisation encore peu utilisé au Québec et montre que son impact sur les consommateurs est généralement positif. Cet outil de marketing pourra aider une entreprise à augmenter ses ventes, à bonifier son image sociale ou à améliorer les relations avec ses employés. Il permettra à l’OSBL-cause sociétale en question d’obtenir un financement additionnel et une visibilité accrue. Il donnera aux consommateurs le sentiment du devoir accompli. La société en entier sera bénéficiaire de cette forme de commercialisation. Certes, le marketing de partage peut mettre en jeu la réputation de l’entreprise. Aussi le choix judicieux d’un OSBL-cause sociétale à soutenir est primordial pour la réussite d’un programme de marketing de partage. Cet article propose un modèle de processus décisionnel de sélection d’un partenaire social.

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)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.341
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.002

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 head0.040
GPT teacher head0.244
Teacher spread0.204 · 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; both teacher heads agree on what is shown here.

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
Published2002
Admission routes2
Has abstractyes

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