Religiosity at the Top and Annual Report Readability
Bibliographic record
Abstract
This paper examines how individual religiosity at the top level of organizations affects the quality of their disclosure practices, as measured by the readability of annual reports. Our paper extends the recent accounting and finance literature that moves away from a location-based measure to an individual-based measure for capturing the effect of religiosity. Our findings suggest that the individual religiosity of C-suite executives matters in corporate decision-making and has positive implications for the quality of corporate disclosure practices, as reflected by more readable reports. This main finding is primarily driven by the religiosity of CEOs. Additional findings also suggest that the effect of religiosity is not solely driven by the religious denomination of the majority group within a given location-based setting. Previous research using religiosity proxies based on the majority religion in the locale of firms’ headquarters may have measurement issues that disguise the effect of religiosity. This issue is particularly problematic when CEOs or other executives participate in minority religious denominations. Overall, our paper finds that CEO religiosity is an important attribute that affects the overall quality of business practice.
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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 | 0.002 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".