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Record W2495631342 · doi:10.22495/cocv13i4p10

Swiss CSR-driven business models extending the mainstream or the need for new templates?

2016· article· en· W2495631342 on OpenAlex
Stéphanie Looser, Walter Wehrmeyer

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCorporate Ownership and Control · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsSurrey Place Centre
Fundersnot available
KeywordsConsistency (knowledge bases)Corporate social responsibilityMainstreamDelphi methodProcess (computing)Business modelCore (optical fiber)Key (lock)BusinessComputer sciencePolitical scienceMarketingPublic relationsArtificial intelligence

Abstract

fetched live from OpenAlex

Many Swiss small and medium-sized enterprises (SMEs) have highly sophisticated Corporate Social Responsibility (CSR) agendas embedded in corporate cultures that nurture a “raison d’être” far beyond formalisation. Previous research culminated in the characterisation of this core logic as “L’EPOQuE”, the overarching SME business model making Switzerland, arguably, a hidden champion in CSR. This paper explored by the method of a two-stage Delphi process the model’s consistency with criteria of conventional business models. It confirmed the core logic of L’EPOQuE and encouraged at the same time slight modifications with regard to nomenclature of sub-features resulting in L’EPOQuE 2.0. This heightened the power of this CSR-driven approach to be a new template for informal set-ups, and niches. It emerges from the difficulties some mainstream business models have to satisfy the needs of business at the nexus of culture and economic rationale.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.739
Threshold uncertainty score0.606

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.084
GPT teacher head0.254
Teacher spread0.170 · 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