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Record W2004967842 · doi:10.1080/0964056032000070990

Sustainability-focused Organizational Learning: Recent Experiences and New Challenges

2003· article· en· W2004967842 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.

Bibliographic record

VenueJournal of Environmental Planning and Management · 2003
Typearticle
Languageen
FieldDecision Sciences
TopicComplex Systems and Decision Making
Canadian institutionsYork University
Fundersnot available
KeywordsTriple bottom lineSustainabilityOrganizational learningBusinessSocial learningProcess managementKnowledge managementOrganizational cultureMarketingPublic relationsComputer sciencePolitical scienceEcology

Abstract

fetched live from OpenAlex

To an increasing extent, corporations and smaller businesses are making explicit commitments to improved environmental and social performance. Some have embraced the goal of sustainability, and some prefer to use the term 'triple bottom line'--a balance of financial, social and ecological performance--in their operations. Some companies are experimenting with organizational learning as a means to accelerate the transition to sustainability or the triple bottom line. This fledgling combination--sustainability and organizational learning--is the focus of this paper. The term 'sustain ability-focused organizational learning' (SFOL) is proposed to describe the early experience of companies that are attempting to pursue sustainability or the triple bottom line while making substantial changes to their organizational cultures. In many instances, these changes involve the use of experimental or unconventional learning techniques. Some companies are combining their SFOL efforts with The Natural Step, a sustainability framework. The experience of five companies pursuing SFOL is summarized and analysed in a non-identifying way, and key preliminary lessons are discussed.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.662
Threshold uncertainty score0.369

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.092
GPT teacher head0.332
Teacher spread0.240 · 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