Corporate social responsibility: a European perspective. Jean Monnet/Robert Schuman Paper Series Vol. 13 No. 6, June 2013
Bibliographic record
Abstract
From the Introduction. CSR grows at different rhythms. CSR varies from continent to continent, country from country, sector from sector and corporation from corporation. The Responsible Competitive Index (RCI) from the UK NGO Accountability and the Brazilian Business School, Fundaçao Dom Cabral, looks at how countries are performing in their efforts to promote responsible business practices and issues periodical indexes about such performances. The RCI’s index for 2007 analysed 108 countries (96% of global GDP). The analysis showed that more advanced economies do better in this area. The top 20 countries, by the ranking order of best performance, were the following: 1 Sweden, 2 Denmark, 3 Finland, 4 Iceland, 5 UK, 6 Norway, 7 New Zealand, 8 Ireland, 9 Australia, 10 Canada, 11 Germany, 12, Netherlands, 13 Switzerland, 14 Belgium, 15 Singapore, 16 Austria, 17 France, 18 USA, 19 Japan, and 20 Hong Kong, etc. However, it is important to bear in mind that advanced economies have often moved their more dirty industries to other parts of the world where there are less stringent environmental and social standards. As a result, other countries may be polluting on their behalf, and the indexes do not factor those in.2
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 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".