Legitimizing Potential “Bad News”: How Companies Disclose on Their Tension Experiences in Their Sustainability Reports
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The practice of corporate sustainability is beset with compromise; it involves inevitable tensions across competing social, environmental, and economic objectives, across a wide range of divergent stakeholders and across time. The purpose of this study is to determine whether, and why, companies are reporting on tensions decisions in their sustainability reports. This study relies on a group of the largest companies in Canada and analyzes sustainability reports and interviews with sustainability managers. The study finds that 92% of all reporting companies in the sample had encountered sustainability tensions but had failed to disclose these discussions explicitly in their reports. Evidence of these accounts are nevertheless present in the implicit (or latent) content of the reports, surrounded by “legitimizing talk”—affirmations of the companies’ commitment to, and demonstration of sustainability principles. These findings highlight the negative light in which many companies perceive tensions (as “bad news”) and the potential legitimacy threat that their disclosure poses.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it