Greenhouse Gas (GHG) Emissions Accounting Systems: Testing the Rationale Behind Corporate Verification Practices
Bibliographic record
Abstract
The total quantity of GHG emissions produced within or beyond the boundaries of a firm's business activities, owned or non-owned, is of a great concern with respect to verification.A carbon accounting system enables an organization to audit its GHG emissions inventory, and it is becoming a standard requirement for most businesses to shape future decision-making.Currently, corporations use GHG emissions inventory data for regulatory compliance, raising capital in the market and reputational assurance.The scholarly and non-academic body of knowledge that deals with the critical aspects of verifying GHG emissions inventories involves using a protocol or a standard to verify an entity's reported inventory.Currently recognized GHG reporting protocols and standards specify acceptable verification methods and emphasize GHG emissions inventory assurance.The goal of this paper is to understand the rationale and relative importance of corporate verification of GHG emissions.We identify the potential drivers underlying corporate GHG emissions verification practices and highlight the governing principles to classify them based on the extant scholarly literature.We studied a sample of the S&P 500 companies that were recognized by the Carbon Disclosure Project (CDP) as best-in-industry for disclosure of GHG emissions information based on the Climate Disclosure Leadership Index (CDLI).A logit model was built to estimate the probability that a company would verify its GHG emissions given the values of the explanatory variables.GHG emissions verification practices data as well as its drivers were collected from the publicly available sustainability or corporate social responsibility reports.The analysis showed that the main drivers for corporate GHG emissions verification include meeting mandatory regulatory requirements and/or complying with voluntary GHG emissions reporting standards as well as responding to emerging requirements for GHG emissions trading programs and stakeholders demand for full disclosure of GHG emissions to demonstrate environmental stewardship and social responsibility.
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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 | 0.125 | 0.355 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".