Sustainability reporting guidelines mapping and gap analyses for Shanghai stock exchange
Bibliographic record
Abstract
IFC and the Shanghai Stock Exchange (SSE) worked with SynTao on a study of existing sustainability reporting guidelines internationally and in China, comparing these with the existing SSE requirements. The study included interviews with key stakeholders and a review of the characteristics of 25 existing international and national frameworks. It confirms that, though sustainability reporting in China has increased in recent years, there is still much work to do to improve the quality and usefulness of environment,social and governance (ESG) information provided to stakeholders, particularly investors. According to Klynveld Peat Marwick Goerdeler, in 2008 79 percent of 250 global companies published sustainability reports. In China the number of sustainability reports reached over 700 in 2010. There is a widely established expectation that companies wanting to obtain a leadership position and become competitive in the global marketplace need to effectively manage their environmental and social performance, disclosing challenges and achievements in a sustainability report. Moreover, corporate product and service innovation should aim to contribute to society's well-being. Studies show that in China, however, most companies release sustainability reports for reasons of reputation and development of government relationships, not fully taking advantage of opportunities for risk management and investor relations. The study included a wide literature review and interviews with a selection of key stakeholders. This report was published in partnership with Canada.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | high |
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 | 0.013 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.015 | 0.017 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".