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Record W3156610810 · doi:10.1002/bse.2788

Does quality management improve the internalization of environmental practices? An empirical study in Africa

2021· article· en· W3156610810 on OpenAlexaff
Christian Valéry Tayo Tene, Olivier Boiral, Iñaki Heras Saizarbitoria

Bibliographic record

VenueBusiness Strategy and the Environment · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicQuality and Management Systems
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsStandardizationBureaucracyQuality (philosophy)BusinessQuality managementEnvironmental resource managementSustainable developmentEnvironmental qualityQuality management systemAccountingProcess managementPolitical scienceEconomicsMarketing

Abstract

fetched live from OpenAlex

Abstract This article analyzes the role of quality management in the internalization of environmental practices. A qualitative study based on interviews with 35 practitioners was conducted in three African countries (Cameroon, Senegal, and Ivory Coast). The results highlight the contrasting roles played by the main reference model for quality management—International Organization for Standardization (ISO) 9001—in the internalization of the international standard for corporate environmental management—ISO 14001—with positive points related to formal and documentary aspects and perverse effects such as increased bureaucracy and a focus on quality at the expense of the environment. The results also point to four configurations of integration of environmental practices according to the level of quality management internalization and the level of institutional pressure to adopt corporate environmental management: poor integration, partial integration, substantial integration, and sustainable integration.

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)0.006
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.003
Scholarly communication0.0020.003
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.042
GPT teacher head0.288
Teacher spread0.245 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations16
Published2021
Admission routes1
Has abstractyes

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