Environmental monitoring of government — the case for an environmental auditor
Bibliographic record
Abstract
In November 1997 the Environmental Audit Committee of the House of Commons (EAC) was established. The Committee is modelled in some ways on the Public Accounts Committee of the House of Commons (PAC) but, unlike the PAC, the EAC is not supported by an independent auditor. This article argues that, despite the limitations of audit made in accountancy literature, audit can be a useful mechanism by which to hold government to account for the impact of its policies and operations on the environment. However, as a model of accountability, the current system of environmental audit is inadequate. In making this argument, the article draws on two existing audit models. First, because the government has chosen to model the EAC on the PAC, the mechanisms in place for securing financial and value for money accountability in UK central government will be considered. Second, the article looks to the arrangements in Canada, where a more developed system of environmental audit exists.
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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 | 0.057 | 0.103 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.020 | 0.035 |
| Scholarly communication | 0.022 | 0.015 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.015 | 0.016 |
| Insufficient payload (model declined to judge) | 0.003 | 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".