Three Models of Corporate Social Responsibility: Interrelationships between Theory, Research, and Practice
Bibliographic record
Abstract
Decades of debate on corporate social responsibility (CSR) have resulted in a substantial body of literature offering a number of philosophies that despite real and relevant differences among their theoretical assumptions express consensus about the fundamental idea that business corporations have an obligation to work for social betterment.All accounts of CSR recognize that business firms have many different kinds of responsibility, and seek to define both the scope of corporate responsibility in society and the criteria for measuring business performance in the social arena. 1 Waddock 2 used the metaphor of a branching tree to describe how the field has evolved into its current understanding of CSR, an understanding that attempts to link the relatively parallel universes of theory and practice, and to illustrate how various conceptual branches are related to each other.Fruitful as the development of a comprehensive organizing framework for the field has been, we are still left with the same quagmire of definitional problems that beclouded the old debate about the exact nature of CSR.The old claim that CSR "means something, but not always the same thing to everybody" 3 is no less true today.This article seeks to add clarity
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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 | 0.034 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.007 | 0.071 |
| Scholarly communication | 0.022 | 0.028 |
| Open science | 0.005 | 0.015 |
| Research integrity | 0.010 | 0.010 |
| 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".