The Extensiveness of Corporate Social and Environmental Commitment across Firms over Time
Bibliographic record
Abstract
Corporate social commitment (CSC) and corporate environmental commitment (CEC) are often combined under the general rubric of corporate social responsibility. Although the two sets of activities are similar, they are also very different. Both CSC and CEC respond to issues raised by stakeholders, but CEC tends to be more “technical”. This characteristic demands that CEC fit with the organization, which exposes greater economic opportunities than CSC. As a result, we argue that the extent to which these practices are implemented differs across firms over time. We analyze the extensiveness of implementation of CSC and CEC across 266 firms from 1991 to 2003, using latent growth curve modeling and one-way ANOVA. We find that firms moved towards at least a moderate level of CSC over time, but tended to bifurcate in the extent to which they implemented CEC practices, towards either the high or low end of the scale, over time. In this paper, we contribute to the institutional analysis of practice diffusion by examining how the characteristics of different kinds of practices shape the extensiveness of firm adoption patterns. As well, this research also speaks to corporate social responsibility researchers, pointing to the need to sometimes discriminate between social and environmental practices.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".