Bibliographic record
Abstract
The relationship between a company’s influence and its social responsibilities is the subject of persistent controversy, manifested for example in the debate over the use of the concept of “sphere of influence” (SOI) to define the scope of a company’s social responsibility. Early drafts of the ISO 26000 guide on social responsibility employed SOI in this way, stating among other things that influence can give rise to responsibility and that generally, the greater the ability to influence, the greater the responsibility. The UN Special Representative on business and human rights, John Ruggie, rejected this use of SOI as ambiguous, misleading, morally flawed, and susceptible to strategic gaming. The final version of ISO 26000 was amended in an effort to accommodate these objections. This chapter examines how the concept of SOI is articulated in ISO 26000 and the extent to which it responds to critics’ concerns. First, ISO 26000 avoids the main source of conceptual ambiguity attributed to SOI, the conflation of “influence as impact” with “influence as leverage,” by defining SOI exclusively in terms of leverage. Second, it avoids the main source of operational ambiguity, the tendency to operationalize SOI in terms of “proximity,” by making it clear that SOI is a relational rather than spatial concept. Third, ISO 26000 is ambivalent on the moral question of whether leverage alone should give rise to responsibility. The chapter distinguishes four varieties of influence-based social responsibility: impact-based negative responsibility, impact-based positive responsibility, leverage-based negative responsibility and leverage-based positive responsibility, and shows that ISO 26000 reflects all four to varying degrees. Finally, ISO 26000 responds partially to the critics’ fourth complaint that the SOI concept leads to strategic gaming.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.013 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".