Integrating Corporate Social Responsibility Into a Corporate Culture, the Quest to Embed Integrity into the Workplace
Bibliographic record
Abstract
Abstract Nexen Inc. (the "Company"), an independent global energy and chemicals company, has made significant strides in the area of corporate social responsibility ("CSR"). Developments such as globalization, environmental issues, competitive labor markets and advances in technology have accelerated the pace at which these and other corporate social responsibility issues have risen up the corporate agenda. The playing field for multi-national enterprises has been forever altered. In response to these emerging issues and encouraged by Canada's Minister of Foreign Affairs, the Company championed and adopted the International Code of Ethics for Canadian Business (the "Code") in 1997. The Code received endorsement from the Canadian government and support from many companies and business associations. The Code provides principles for community participation, environmental protection, business conduct and employee health and safety. The Company's Integrity Program is the vehicle by which the Code is implemented. The Integrity Program focuses on ensuring that the Code is more than simply words. Its principles have been successfully translated into comprehensive and innovative practices which address industry considerations faced by companies today and which benefit the company and its stakeholders. Corporate social responsibility is an area of emerging global importance. Besides being the right thing to do, fostering a culture of integrity has ensured that the Company adds shareholder value over the long term and makes a difference in its broader sphere of influence.
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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 | 0.016 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.057 |
| Scholarly communication | 0.023 | 0.008 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.005 | 0.007 |
| 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".