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Record W2145714564 · doi:10.7202/039547ar

Stratégies RSE-BOP et Soin des Communautés Humaines. Concepts et Propositions Génériques

2010· article· fr· W2145714564 on OpenAlexvenueno aff
Marielle Audrey Payaud, Alain Charles Martinet

Bibliographic record

VenueManagement international · 2010
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicInnovation and Socioeconomic Development
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesSociologyPhilosophy

Abstract

fetched live from OpenAlex

Parmi les nombreuses pratiques de stratégies de responsabilité sociale, l’une requiert un engagement fort de l’entreprise sur le territoire, c’est-à-dire de ses compétences, de sa gouvernance et de son management : la RSE-BOP (Martinet, Payaud, 2008a, 2008b, 2009). La RSE-BOP est inspirée de « La base de la pyramide » (« Bottom of the pyramid ») de Prahalad (2004) qui désigne les 4 milliards d’individus disposant de moins de deux dollars par jour et qui suggère aux entreprises de reconsidérer ce faible pouvoir d’achat et de s’intéresser à ces nouveaux consommateurs. L’article esquisse un cadre conceptuel destiné au management stratégique de projets d’entreprise s’inscrivant dans une telle perspective. Ainsi, il présente la RSE-BOP comme une forme avancée de la RSE et une voie pour l’aide au développement des pays les plus pauvres, développe les fondements théoriques du cadre conceptuel et les conditions de mise en oeuvre d’une RSE-BOP.

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)0.005
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.014
Scholarly communication0.0080.008
Open science0.0010.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.022
GPT teacher head0.304
Teacher spread0.282 · 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 designTheoretical or conceptual
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

Citations19
Published2010
Admission routes1
Has abstractyes

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