Alleviating the corporate social responsibility reporting-performance inconsistency : a tentative proposal of the "reflexive law plus" model
Bibliographic record
Abstract
The present research identifies corporate reporting-performance inconsistency as a major issue that undermines the current practice of corporate social responsibility (CSR). The inconsistency manifests in that companies either avoid disclosing negative information in their CSR reports or use vague and empty expressions to cover their CSR inaction. In most situations, instead of providing a complete and balanced picture and causing companies to re-examine their own CSR behaviour, CSR reporting has been declining into a strategic corporate communication tool that primarily serves firms’ own interests. Such a problem greatly challenges the fundamentals of CSR and raises hard questions as to the reliability of private regulation and corporate self-regulation pertaining to CSR reporting. Taking Canada as a field of research, the present study combines theoretical with empirical research methodology in order to thoroughly investigate the problem of the CSR reporting-performance inconsistency and provide a plausible solution to it from a law and regulation perspective. The main empirical research methods it takes are qualitative interviews and documentary analysis. In particular, the present research builds on the literature and empirical observations to explain the inconsistency and identify the regulatory gaps that currently exist in CSR reporting. As a side issue, it also questions the primary purpose of the CSR reporting regime, suggesting that CSR reporting should be used to transform irresponsible corporate performance and serve broader public goals. Inspired by the reflexive law literature and the empirical evidence, the present research develops a concrete model of “reflexive law plus” to address the CSR reporting-performance gap. “Reflexive law plus”, as named by the present research, is a refined form of reflexive law, in the sense that it is faithful to the fundamentals of the reflexive law theory, yet incorporates regulatory design components that can better catalyze and consolidate the self-referential capacity of the companies involved in CSR reporting. The present research holds that “reflexive law plus” provides a sound solution to remediate the inconsistency because it is pertinent to the regulatory circumstance in which CSR reporting is situated.
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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 | 0.025 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.027 |
| Scholarly communication | 0.010 | 0.018 |
| Open science | 0.006 | 0.010 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 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".