Toward holistic corporate sustainability—Developing employees' action competence for sustainability in small and medium‐sized enterprises through training
Bibliographic record
Abstract
Abstract To advance holistic corporate sustainability in small and medium‐sized enterprises (SMEs) requires employees to fully engage in sustainability efforts, which, in return, means to develop employees' action competence for sustainability. Little empirical evidence, however, exists on how to do this considering well‐known constraints SMEs face (time, expertise, resources). We present a transdisciplinary project that developed, delivered, and evaluated a sustainability training for the workforce of the Bohlsener Mühle, an SME that has pioneered corporate sustainability in Germany. The training was piloted for the business' apprentices and combined different learning modes to build participants' sustainable action competence. The pre‐post evaluation, supported by observations and qualitative interviews, revealed that employees' action competence for sustainability can be fostered through such trainings and is most effective if organizational factors that enable a corporate culture of sustainability are aligned. We conclude that a human‐centered and action‐oriented approach to training is needed to unleash the full potential of the workforce to advance corporate sustainability.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".