Corporate social and environmental disclosure in developing countries: Evidence from Iran
Bibliographic record
Abstract
Article history: Received April 23, 2012 Received in revised format 22 October 2012 Accepted 26 October 2012 Available online October 31 2012 This research aims to investigate the extent of social and environmental disclosure (SED) in corporate annual reports. Specifically, This is an exploratory study designed to examine the relationship between corporate social and environmental disclosure (CSED) and corporate attributes and firm-specific factors in a developing country, Iran. In order to do this, we use content analysis approach with sentence count for the level of disclosure measurement by looking into the annual reports of the 66 listed companies in Tehran Stock Exchange. The Panel analysis and econometric software EVIEWS 6 are used for analyzing data. The Results show that there is significant positive relationship between company size and level of CSED also there is significant negative relationship between environment sensitive industries and level of CSED. However, we did not find any relationship between profitability and the level of CSED. © 2013 Growing Science Ltd. All rights reserved.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".