Swiss CSR-driven business models extending the mainstream or the need for new templates?
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.028 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.012 | 0.017 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".