Bibliographic record
Abstract
Abstract Having a Code of Ethics (COE) has become a common practice within large companies since the 1980s. A COE serves multiple functions for organizations: as an internal control mechanism to guide employees during ethical dilemmas, a benchmark for fostering ethical corporate culture, and as a communication tool to signal organizational commitment to stakeholders. Four major theoretical frameworks underpin the extant academic scholarship on COEs. In particular, organizational justice and stakeholder theories highlight the role of individuals in adopting and shaping a COE, and the institutional theory emphasizes the influence of the exogenous environment on the convergence and/or divergence of COEs across firms and contexts. Integrative social contracts theory captures the significance of both individuals and the institutional environment and views COEs as a contractual obligation that guides managers and employees to manage contradictions between local and global norms. Within these theoretical framings, significant variations in the nature and stakeholder orientations of COEs have been detected across the developed and developing world. In the developed contexts, a comparative institutional analysis using the national business system approach shows that while in the compartmentalized cluster (the United States, United Kingdom, Canada, Australia, and Japan), expectations of market participants and firm owners are key drivers of COEs; in the collaborative cluster (Germany, Ireland, and the Netherlands), firms develop COEs that have a wider focus oriented towards multiple stakeholders such as employees, suppliers, and the environment. Whereas in the state-organized cluster (South Korea, Spain, Greece, and Slovakia) the role and the nature of the state are important guiding factors. The coordinated industrial district cluster (Italy) characterized by alliances among smaller artisanal firms demonstrates a human-centric view of business embedded within their COEs. Excluded from the national business systems categorization, the Nordic cluster displays a unique distinctiveness in its approach to COEs through the presence of a structured moral apparatus within firms. In the developing world, country-specific institutional characteristics play a vital role behind adoption of localized a COE, yet nonstate actors—namely multinationals enterprises, and international and supranational institutions—promote the diffusion of hyper-norms. Given the pervasiveness of corporate misconduct despite the global diffusion of COEs, scholars must pay heed to understand the conditions under which gaps between a COE adoption and implementation arise. Equally, more scholarly attention needs to be accorded to a systematic investigation of COEs in transitional and emerging contexts. This becomes particularly necessary in the face of sociological changes, a fast-evolving landscape of local and transnational regulations including those arising from global events such climate change, and COVID-19, and the co-existence of multilevel COEs at the industry, firm, and professional levels.
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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 | 0.021 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.007 | 0.039 |
| Scholarly communication | 0.016 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".