GESTÃO DA SUSTENTABILIDADE NAS ORGANIZAÇÕES: UMA ANÁLISE DOS PARÂMETROS, DESAFIOS E POSSIBILIDADES ENCONTRADOS NO BRASIL E NO CANADÁ
Bibliographic record
Abstract
Na literatura sobre sustentabilidade estao presentes, de uma forma mais consolidada, as exigencias, os indicadores, os efeitos, a historia e a critica de seu conceito e pratica. No entanto, uma analise aprofundada sugere a insuficiencia de tal estado da arte para responder questoes sobre como articular conceitos sistemicamente para que a sustentabilidade se torne parte efetiva das acoes e decisoes organizacionais. Com isso, lanca-se aqui o intento de estudar as experiencias canadenses com os desafios e as possibilidades encontrados para tornar a sustentabilidade parte efetiva da gestao organizacional. O presente artigo, de carater exploratorio-descritivo, foi realizado a partir de consultas a projetos, documentos, experiencias e entrevistas com profissionais da University of Western Ontario – UWO - CA, em especifico na sua Escola de Negocios - Ivey Business School, e em dois orgaos a ela vinculados, a Network for Business Sustainability e o Building Sustainable Value Research Centre . Espera-se que os resultados sumarios deste intento investigativo, o qual e parte de um projeto maior financiado pelo CNPq, permita a reflexao sobre o campo da sustentabilidade no Canada e sua sequente circunscricao das referencias estudadas para compara-las com estudos brasileiros, ampliando, com isso, as possibilidades de analises sobre as lacunas emergentes sobre o tema.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.016 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".