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Record W4210462385 · doi:10.3934/gf.2022004

Carbon Accounting: A Systematic Literature Review and Directions for Future Research

2022· article· en· W4210462385 on OpenAlex
Jillene Marlowe, Amelia Clarke

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

VenueGreen Finance · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEnvironmental Sustainability in Business
Canadian institutionsUniversity of WaterlooMemorial University of Newfoundland
Fundersnot available
KeywordsComparabilityAccountingTransparency (behavior)Greenhouse gasReliability (semiconductor)Accounting researchSystematic reviewPolitical scienceBusinessMEDLINEEcologyPhysics

Abstract

fetched live from OpenAlex

<abstract> <p>Carbon accounting is an evolving approach to support decision-making for climate action and reporting of progress. This systematic literature review of 27 journal articles in the field of carbon accounting provides an overview of the current state of the field. It illustrates the lack of transparency, reliability, and comparability within current measurement systems; the lack of research on how greenhouse gas inventories are linked to monitoring, decision-making, reporting and disclosure systems; and the role of the accounting profession. Based on the findings, we provide a summary of where research gaps exist and thus suggestions for future research directions.</p> </abstract>

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.910
Threshold uncertainty score0.594

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.018
GPT teacher head0.261
Teacher spread0.243 · 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