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Record W4386298391 · doi:10.18174/634814

Hoe True Cost Accounting bijdraagt aan het meten van Brede Welvaart : Begrippen True Pricing, True Cost Accounting, MKBA en Brede Welvaart toegelicht

2023· report· nl· W4386298391 on OpenAlexaff
E.B. Oosterkamp, H.J. Silvis, Katja Logatcheva

Bibliographic record

Venuenot available
Typereport
Languagenl
FieldEnvironmental Science
TopicEnvironmental Conservation and Management
Canadian institutionsImpact
Fundersnot available
KeywordsEconomicsCost accountingSustainabilityAccountingManagement accounting

Abstract

fetched live from OpenAlex

Based on literature search and some interviews this report explains the relation between the concepts of True Price, True Cost Accounting en general welfare. True Cost Accounting/True Price are comparable with the Brede Welvaart ‘later’ (General welfare ‘sustainable’) monitor of Statistics Netherlands that monitors the sustainability of a country or region. True Cost Accounting/True Price monetises sustainability of agricultural activities. In doing so it is also a kind of societal cost-benefit analysis.

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)0.004
metaresearch head score (Gemma)0.011
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.144
Threshold uncertainty score0.287

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.006
Science and technology studies0.0010.001
Scholarly communication0.0130.007
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0180.004

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 head0.046
GPT teacher head0.298
Teacher spread0.252 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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