Corporate Sustainability Distinctions, Transitions and Perceptions: A Look to Canada’s Big Five Banks
Bibliographic record
Abstract
Corporate sustainability (CS) is becoming increasingly mistaken for or confused with corporate social responsibility (CSR). Literature in recent years has identified this muddied area and argues for further clarity. Clarifying this confusion and understanding the fundamentals of CS can help to ensure companies implement sustainable strategies that are beneficial for current and future generations, while also ensuring resiliency and long-term success. With the creation of a theoretical framework that sets CS and CSR apart, this research emphasizes the importance of sustainability within business and explores Canada’s Big Five banks as its case study. Through the analysis of 75 past and present reports (2002-2018), as well as interviews with employees of all five companies, the ways in which sustainability and social responsibility are perceived and implemented is investigated. Findings demonstrate clear shifts beyond CSR towards greater focus on CS within Big Five operations, allowing for lessons to be learned across sectors.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".