Similar But Not the Same: Differentiating Corporate Sustainability from Corporate Responsibility
Bibliographic record
Abstract
Corporate responsibility and sustainability tackle the relationship between business and society. However, the two fields of study have converged to become deeply entangled and blurred so that researchers from both research traditions now speak to the same business risks and opportunities. A field’s development is shaped by the clarity of its constructs and underlying assumptions; however, such clarity has eroded in responsibility and sustainability research. By tracing the development of these fields, we show that responsibility and sustainability were historically distinctive. Responsibility research took a normative position, railing against the amorality of business; sustainability research took a systems perspective, sounding the alarm of business-driven failures in natural systems. The convergence in responsibility and sustainability has not only confused constructs but has also vacated vast tracts of unexplored territory that can inform the relationship between business and society. By sharpening the distinctiveness between responsibility and sustainability, we call for further research to deepen the areas of research unique to each of these two fields of study and explore their complementarities and intersections.
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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 | 0.014 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.004 | 0.040 |
| Scholarly communication | 0.015 | 0.023 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| 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".