Environmental performance auditing by supreme audit institutions: progress, practice and prospects
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.
Bibliographic record
Abstract
Environment and sustainable development challenges are matters of global concern. Trillions of dollars of mostly public money are invested every year in environment programs to address these challenges. The effectiveness of these programs is critical to environmental sustainability. The effectiveness of governments’ programs is examined through evaluations undertaken mostly by the private sector and through performance audits undertaken by independent Auditors General, also known as supreme audit institutions (SAIs). Compared with traditional evaluations, performance audits have a greater capacity to influence the implementation of policies. However, performance auditing in the environment field has received very little academic attention. To fill this knowledge gap, this thesis undertakes three empirical investigations: (1) A longitudinal analysis of two decades (1992-2012) of global environmental performance audit data that also considers some economic data, e.g., gross per-capita national income, to investigate trends; (2) A global survey of SAIs to investigate their current practices and challenges faced in environmental performance auditing; and (3) A comparative study of environmental performance auditing in three countries—Australia, Canada and India—to further understand environmental performance auditing. The results suggest that, globally, environmental performance audits have been growing, in number and possibly complexity. However, the growth has been uneven. About half of SAIs have not produced any environmental performance audits, suggesting capacity gaps. These SAIs are largely concentrated in Africa and Caribbean—two economically poor regions. Both a country’s economic development, and its membership of the Working Group on Environmental Auditing (WGEA) are correlated to environmental performance auditing. SAIs, predominantly, select environmental topics for performance auditing using a risk-based structured approach. Performance audits criteria are generally developed in consultation with auditees. Economic factors influence the choice of audit topics and methods. Generally, the developed country SAIs focus on performance auditing of quality of life environmental issues, such as climate change, whereas, the developing country SAIs concentrate on subsistence environmental matters, such as water supply and sanitation. Compared with developing SAIs, developed SAIs generally use more system-oriented approaches and are more consultative. SAIs identify both the lack of sufficient mandate and sufficient resources as constraints to undertaking more environmental performance audits. Institutional arrangements do affect environmental performance auditing. Significant variations in reporting styles of performance audits are a consequence of deficient quality control and an absence of reporting standards. Key challenges confronting environmental performance auditing relate to: (a) Deficient environmental policy formulation and data & monitoring difficulties (governments responsible); (b) SAIs’ mandate & resources (governments responsible); and (c) Audit relationships and communication matters (SAIs responsible). While environmental performance audits have had positive impacts on the implementation of environmental programs, actions for improvements are necessary to meet the growing challenges of the future, including implementing the new sustainable development goals. These include: • Capacity building in performance auditing especially in poor countries (donor agencies, governments); • Addressing deficiencies in environmental policies and mandate & resources of SAIs (governments); • Working collaboratively with others, e.g., civil society organisations, to develop innovative audit methods; and improving reporting standards & communication (SAIs); and • Strengthening the WGEA (SAIs).
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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 it