Beyond the Horizon: The Future of Corporate Social Responsibility
Bibliographic record
Abstract
As the Canadian corporate landscape continues to evolve, traditional models of corporate social \nresponsibility (CSR) are facing increasing scrutiny and calls for transformation. This paper \nexplores the necessity of rethinking these conventional approaches and embracing new \nparadigms to ensure future preparedness in the corporate world. By shifting the focus from \nsolely measuring success based on profitability to encompassing a broader range of metrics, \nincluding climate justice, human rights, and collective liberation, organizations can better \naddress the complex challenges of the modern era. Drawing on insights from literature review \nand secondary research, this paper advocates for a comprehensive approach to CSR that \nprioritizes the well-being of the planet, people, and purpose. Through this reimagining of CSR, \nbusinesses can not only enhance their sustainability and resilience but also contribute to the \ngreater good of society and the environment.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.013 | 0.041 |
| Scholarly communication | 0.022 | 0.014 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".