An integrated Approach for Corporate Social Responsibility and Corporate Sustainability
Bibliographic record
Abstract
Balance of power has shifted between the state, society and corporations, which gave birth to the concepts like corporate social responsibility (CSR) and corporate sustainability (CS). Due to the common grounds of CSR and CS, confusion has been created among academics as well as practitioners. This study seeks to identify the relationship between CSR and CS by providing a framework in order to get a better understanding of them. In addition to reviewing the extant literature, we provided empirical support through interviews of CSR or sustainability managers of large New Zealand companies. The key findings of this research revealed that when CSR and CS applications were based on systematic and full fledge focus, there was almost similar kind of initiatives and practices in NZ corporations. To develop an approach to integrating CSR and CS, we support the term, Corporate Sustainability and Responsibility (CS-R). We believe that CS-R help define and clarify the relationship between business and society without denying the great success that CSR has achieved in the academic research, management consulting and media.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.004 | 0.029 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".