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Record W1603683328 · doi:10.4324/9781351281287

Business and Human Rights

2017· book· en· W1603683328 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typebook
Languageen
FieldSocial Sciences
TopicHuman Rights and Development
Canadian institutionsnot available
Fundersnot available
KeywordsHuman rightsBusinessLaw and economicsPolitical scienceSociologyLaw

Abstract

fetched live from OpenAlex

Foreword Mary Robinson, Executive Director, Ethical Globalisation Initiative former United Nations High Commissioner for Human Rights 1. Introduction Rory Sullivan, Insight Investment, UK 2. The evolution of the business and human rights debate Sir Geoffrey Chandler, UK 3. The of human rights responsibilities for multinational enterprises Peter Muchlinski, University of Kent at Canterbury, UK 4. Human rights, trade and multinational corporations David Kinley and Adam McBeth, Castan Centre for Human Rights Law, Monash University, Australia 5. Human rights and business: an ethical analysis Denis G. Arnold, University of Tennessee, USA 6. The ability of corporations to protect human rights in developing countries Frans-Paul van der Putten, Gemma Crijns and Harry Hummels, Nyenrode University, The Netherlands 7. What is the attitude of investment markets to corporate performance on human rights? David Coles, Just Pensions, UK 8. From the inside looking out: a management perspective on human rights Rory Sullivan, Insight Investment, UK, and Nina Seppala, Warwick Business School, UK 9. Corporate social responsibility failures in the oil industry Charles Woolfson, University of Glasgow, UK, and Matthias Beck, Glasgow Caledonian University, UK 10. Mining in conflict zones Simon Handelsman, Global Issues Advisors, USA 11. Health, business and human rights: the responsibility of health professionals within the corporation Norbert Goldfield, 3M Health Information Systems, USA 12. Privatising infrastructure development: development refugees and the resettlement challenge Christopher McDowell, Macquarie University, Australia 13. The contribution of multinationals to the fight against HIV/AIDS Steven Lim and Michael Cameron, University of Waikato, New Zealand 14. Elimination of child labour: business and local communities Bahar Ali Kazmi and Magnus Macfarlane, Warwick Business School, UK 15. SA8000: human rights in the workplace Deborah Leipziger, consultant, The Netherlands, and Eileen Kaufman, Social Accountability International, USA 16. Corporate responsibility and social capital: the nexus dilemma in Mexican maquiladoras Luis Reygadas, Universidad Autonoma Metropolitana Iztapalapa, Mexico 17. From fuelling conflict to oiling the peace: harnessing the peace-building potential of extractive sector companies operating in conflict zones Jessica Banfield, International Alert, UK 18. Extracting conflict Gary MacDonald, Monkey Forest Consulting Ltd, Canada, and Timothy McLaughlin, independent consultant, USA 19. Managing risk and building trust: the challenge of implementing the Voluntary Principles on Security and Human Rights Bennett Freeman, Former US Deputy Assistant Secretary of State for Democracy, Human Rights and Labor, and Genoveva Hernandez Uriz, European University Institute, Italy 20. Taking responsibility for bribery: the multinational corporation's role in combating corruption David Hess, University of Michigan Business School, USA, and Thomas Dunfee, University of Pennsylvania, USA 21. Taking the business and human rights agenda to the limit? The Body Shop and Amnesty International Make Your Mark campaign Heike Fabig, University of Sussex, UK, and Richard Boele, Australian Institute of Corporate Citizenship 22. Moving forwards Rory Sullivan, Insight Investment, UK Bibliography

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.105
Threshold uncertainty score0.352

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0040.007
Scholarly communication0.0130.009
Open science0.0010.004
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.1050.068

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.

Opus teacher head0.038
GPT teacher head0.314
Teacher spread0.275 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

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Citations35
Published2017
Admission routes1
Has abstractyes

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