MétaCan
Menu
Back to cohort
Record W4300863960 · doi:10.4324/9781003003588

The Role of Business in Global Sustainability Transformations

2022· book· en· W4300863960 on OpenAlexfundno aff
Dalia D’Amato, Anne Toppinen, Robert Kozak

Bibliographic record

Venuenot available
Typebook
Languageen
FieldEnvironmental Science
TopicSustainable Development and Environmental Policy
Canadian institutionsnot available
FundersHORIZON EUROPE Framework ProgrammeSuomen YmpäristökeskusSNS Nordic Forest ResearchHELSUS Kestävyystieteen InstituuttiOak Ridge Institute for Science and EducationKoneen SäätiöHorizon 2020 Framework ProgrammeNordForskNorth Carolina State UniversityStrategic Research CouncilHelsingin YliopistoSapienza Università di RomaKillam Trusts
KeywordsSustainabilityBusinessProcess managementEcology

Abstract

fetched live from OpenAlex

Drawing on contributions from more than thirty scholars and experts in the field, this book examines the role of business as an enabler, as an inhibitor, and ultimately as a co-actor in global sustainability transformations expected over the next few decades. The Role of Business in Global Sustainability Transformations employs several theoretical perspectives and provides abundant examples and cases to discuss a variety of emerging concepts, phenomena, and trends shaping business sustainability. Weaving through the chapters, the editors present core tensions and sources of inertia towards transformative change, and acknowledge that envisioning multiple solutions and pathways are possible and desirable. They advocate for the need to align visions, actions and time horizons between policy, society and business in addressing the interlinked socio-ecological challenges that our society currently faces. This book will be an important resource for scholars and professionals working in the field of sustainability and sustainable business, and a vital educational text for students interested in this discipline.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.007
Scholarly communication0.0110.008
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.002

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.

Opus teacher head0.003
GPT teacher head0.198
Teacher spread0.195 · 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".

Quick stats

Citations15
Published2022
Admission routes1
Has abstractyes

Explore more

Same topicSustainable Development and Environmental PolicyFrench-language works237,207