A meta-analytical study of cultural conditions moderating the relationship between environmental performance and environmental disclosure
Bibliographic record
Abstract
Purpose This study aims to examine the moderating effect of cultural conditions on the relationship between environmental performance and environmental disclosure. Design/methodology/approach The authors used meta-analysis technique to examine 100 effect sizes from 43 studies published between 1982 and 2023 to integrate the existing results and to detect causes contributing to variability of results across studies. Findings There is a significant positive relationship between environmental performance and environmental disclosure. Further, the authors found that cultures with long-term orientation positively moderated the relationship, whereas cultures with high uncertainty avoidance and indulgence negatively moderated it. Research limitations/implications This study did not account for the problem of endogeneity between environmental performance and environmental disclosure because most of the already published studies included in the authors’ meta-analysis did not address this issue. Practical implications This research provides regulators and policymakers insights on the influence of cultural factors on environmental disclosure and performance, critical information to consider when adopting, or revising social and environmental policy and regulations within a country. Originality/value To the best of the authors’ knowledge, this is the first meta-analysis study examining different cultural dimensions influencing the relationship between environmental performance and environmental disclosure and contributes new knowledge to the literature on determinants of environmental disclosure.
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.
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 | 0.038 | 0.099 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.032 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".