Social impact as a measure of fit between firm activities and stakeholder expectations
Bibliographic record
Abstract
Institutional investors are increasingly focusing on firms that prioritise Corporate Social Responsibility (CSR). In the absence of any objective measure of a firm's CSR Performance (CSP), their investment choices are largely guided by independent rating indices that rank firms according to their social performance metrics. As a result, firms looking to increase their attractiveness as targets of social investment focus their CSR efforts on increasing the visibility of activities that are recognised by such indices. However, the validity of these indices as accurate measures of firms' actual social performance has repeatedly been called into question. This means that the ability of these indices to measure and report on firms' actual social impact cannot be ascertained with any degree of accuracy. The result is that firms are incentivised to engage in activities (whether genuine or 'greenwashing') that cannot be said to improve social responsibility, and may even ultimately harm society. Thus, another method of measuring CSP must be found that enables firms to measure their true impact on society. We propose a new approach to measuring CSP that is integrated with stakeholder theory. Such an approach provides managers of firms with an interest in engaging in real social development for the purposes of ensuring firm survival with the ability to understand their social obligations, and the ability to measure the resulting benefit to society.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".