Sustainability reporting: external motivators and internal facilitators
Bibliographic record
Abstract
Purpose – The purpose of this study is to investigate the role of internal variables, such as strategic governance and operational controls, along with external variables that influence sustainability reporting. Design/methodology/approach – Building on the corporate governance and sustainability reporting literature, the authors develop a model to integrate external motivators and internal facilitators to determine their impact on sustainability reporting. The authors also control for a number of financial and non-financial variables that may influence sustainability reporting. The authors limit their sample to the companies in extractive industries that report their greenhouse gas emission to the Government of Canada. The authors collected the data from several data sources including secondary archival databases, newspapers, Web sites and annual reports. Findings – Using a sample of companies in high-polluting industries, the authors found that variables representing both external pressures that act as motivators and internal controls that act as facilitators are significantly associated with enhanced sustainability reporting. Practical implications – Considering the formation of several international initiatives such as International Integrated Reporting Council to improve sustainability reporting for decision-making, the authors’ research provides interesting insights both to policymakers and managers about organizational characteristics that are important to make reporting useful and relevant. Originality/value – Little academic research has investigated the role of internal variables in facilitating sustainability reporting. The authors use a robust model that combines external and internal variables to more thoroughly understand the reporting process.
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 | 0.018 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".