Do political connections and Environmental, Social, and Governance (ESG) performance affect the relationship between climate change risk and audit efforts?
Bibliographic record
Abstract
The influence of climate risk disclosures on audit engagements remains unclear, largely due to a scarcity of empirical evidence regarding their effect on audit efforts. This study addresses this gap by examining the impact of climate risk disclosures on auditors’ workload. Additionally, it investigates whether political connections and Environmental, Social, and Governance (ESG) performance moderate this relationship within emerging markets in Egypt. The analysis uses data from non-financial companies listed on the Egyptian Stock Exchange between 2017 and 2022. Multiple regression models were developed to test the research hypotheses. Results reveal that greater climate risk disclosure prompts auditors to exert increased effort. Furthermore, this effect is amplified in companies with political connections and higher ESG performance. Robustness tests, employing alternative measures of climate risk disclosure, confirm these findings.
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How this classification was reachedexpand
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 | 0.002 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".