MétaCan
Menu
Back to cohort

Environmental Management, Measurement, and Accounting: Information for Decision and Control?

2011· book· en· W1513309235 on OpenAlexaff
Nola Buhr, Rob Gray

Bibliographic record

VenueOxford University Press eBooks · 2011
Typebook
Languageen
FieldDecision Sciences
TopicComplex Systems and Decision Making
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsEnvironmental accountingManagement control systemEnvironmental management systemManagement accountingEnvironmental resource managementAccounting information systemHarmony (color)BusinessEnvironmental full-cost accountingControl (management)Knowledge managementAccountingAccounting managementComputer scienceThroughput accountingEconomicsManagementEcology

Abstract

fetched live from OpenAlex

This article investigates the nature and detail of environmental management systems. It explores how environmental management systems and the organization's management control systems might (or might not) be brought into harmony. The relationship between environmental management systems, environmental management accounting, and the natural environment are explained. The level of integration between environmental management systems and management control systems depends upon the strategy and objectives of the organization and the status of the environment. As long as win-win opportunities exist, the development and integration of environmental management systems and management control systems is a clear imperative. Full-cost accounting is considerably more demanding than environmental accounting and even more subjective. Despite pessimism (or perhaps it is just realism), one have an abiding belief in the importance of understanding humanity's relationship with the natural environment and the role that environmental management accounting and environmental management systems can play in that relationship.

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)0.014
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: none
Teacher disagreement score0.014
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.011
Science and technology studies0.0010.008
Scholarly communication0.0140.019
Open science0.0010.003
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0110.004

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 head0.085
GPT teacher head0.260
Teacher spread0.174 · 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
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueOxford University Press eBooksSame topicComplex Systems and Decision MakingFrench-language works237,207