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Record W3146741239

The Oxford Handbook of Business and the Natural Environment

2013· article· en· W3146741239 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueOUP Catalogue · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEnvironmental Sustainability in Business
Canadian institutionsWestern University
Fundersnot available
KeywordsManagementPoliticsSociologyEnvironmental ethicsPolitical scienceLawEconomics
DOInot available

Abstract

fetched live from OpenAlex

Environmental issues now loom large on the social, political, and business agenda. Over the past four decades, "corporate environmentalism" has emerged and been constantly redefined, from regulatory compliance to more recent management conceptions such as "pollution prevention", "total quality environmental management", "industrial ecology", "life cycle analysis", "environmental strategy", "environmental justice, " and, most recently, "sustainable development." As a result, understanding the intersection of business activity and environmental protection has become increasingly complex, and there has emerged a focus in academic research on business decision-making, firm behavior, and the protection of the natural environment. This Handbook reviews the state of the field as it grows into a mature area of study within management science, its achievements, and its future avenues of research. It brings together original contributions in the field along several lines of enquiry. The first six focus on disciplines as delineated in contemporary business schools: business strategy; policy and non-market strategies; organizational theory and behavior; operations and technology; marketing; and accounting and finance. The seventh section reviews emergent and associated perspectives, whilst a concluding section, written by long-standing leaders in the field, discusses the future outlook for research. Contributors to this volume - Michael V. Russo, University of Oregon Amy Minto, University of Oregon Petra Christmann, Rutgers University Glen Taylor, California State University Mike Lenox, University of Virginia Jeffrey G. York, University of Colorado George Kassinis, University of Cyprus Andrew King, Tuck School of Business Andrea M. Prado, Stern School of Business Jorge Rivera, George Washington University David P. Baron, Stanford Graduate School of Business Tom P. Lyon, University of Michigan Cary Coglianese, University of Pennsylvania Ryan Anderson Lisa L. Shu, Harvard University Max H. Bazerman, Harvard University Leigh Plunkett Tost, Duke University Kimberly A. Wade-Benzoni, Duke University Jennifer Howard-Grenville, University of Oregon Stephanie Bertels, Simon Frazer University Michael Lounsbury, University of Alberta Samantha Fairclough, University of Alberta Min-Dong Paul Lee, University of South Florida Magali A. Delmas, UCLA Michael W. Toffel, Harvard Business School Klaus Weber, Northwestern University Sara B. Soderstrom, Northwestern University Robert D. Klassen, Ivey Business School Stephan Vachon, HEC Montreal James D. Abbey, Pennsylvania State University V. Daniel R. Guide, Jr., Pennsylvania State University Reid Lifset, Yale University Frank Boons, Erasmus University Nigel P. Melville, University of Michigan Debra Scammon, University of Utah Jenny Mish, Notre Dame Andrew Gershoff, University of Texas, Austin Julie R. Irwin, University of Texas, Austin Timothy M. Devinney, University of Technology, Sydney Irene Herremans, Calgary Robert Gray, University of St Andrews Nola Buhr, Saskatchewan Charles Cho, Concordia University Dennis Patten, Illinois State University Robin Roberts, University of Central Florida Rob Bauer, Maastricht University Jeroen Derwall, Tilburg University Jean-Louis Bertrand, ESSCA Ecole de Management Bernard Sinclair-Desgagne, HEC Montreal Bryan Routledge, Carnegie Mellon University Krista Bondy, Cranfield University Dirk Matten, York University James E. Post, Boston University Linda C. Forbes, Western Connecticut State University John M. Jermier, University of South Florida Subhabrata Bobby Banerjee, University of Western Sydney David L. Levy, University of Massachusetts Benyamin B. Lichtenstein, University of Massachusetts John R. Ehrenfeld, MIT Nigel Roome, Tilburg University Paul Shrivastava, Concordia University John Elkington, SustainAbility and Volans Charmian Love, Volans Stuart L. Hart, Cornell University Thomas N. Gladwin, University of Michigan

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.322
Threshold uncertainty score0.415

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.005
GPT teacher head0.166
Teacher spread0.161 · 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