Organisations beyond Brundtland: A Definition of Corporate Sustainability Based on Corporate Values
Bibliographic record
Abstract
Although a plethora of alternatives exist, companies often base their sustainability efforts more or less explicitly on the definition of the Brundtland Commission. There are, however, conceptual problems when this definition is removed from its original context, in which it addresses social policies and state institutions. In particular the notions of “needs of the present” and “future generations” reveal the qualitative differences between the socio-political context of the Brundtland Commission and the corporate context. In this paper, we explore the entailing dilemmas, argue why current approaches to solve them are insufficient and analyse common practices for sustainability-related statements of 50 companies in Switzerland. The results support the argument that companies tend to avoid a specific definition of corporate sustainability or transpose the Brundtland definition, instead. Both approaches are inappropriate as guiding principles for corporate policy. Instead, we propose basing the concept of sustainability on the broad premise that “the future is a better, healthier place than the present”, specified and substantiated using functionally formulated corporate values. These corporate values and the vision of a “better place” derived from them gear corporate sustainability efforts towards restitution and/or compensation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.021 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".