Strategic posture, financial performance and environmental disclosure
Bibliographic record
Abstract
Purpose The objective of this paper is to test Ullmann's hypothesis that strategy posture, modified by financial performance, must be considered in light of stakeholder power in order to understand a company's social responsibility disclosure policy. Design/methodology/approach This study in this paper uses regression analysis to examine annual report disclosure of environmental information after a major accident in the mining industry. A multiple‐item disclosure score is tailored to the Canadian accounting environment, and used as a dependent variable. Findings This paper finds that companies that maintain themselves in the public eye through press release activity disclose more information than other companies. However there is no evidence to suggest that disclosure content is moderated by financial performance. Companies that obtained external financing one year after the accident made more disclosure than other companies. The significance of the external financing variable is evident when disclosure is restricted to discretionary or non‐financial items, but disappears if the dependent variable represents mandatory financial items. Research limitations/implications The paper shoes that while Ullmann addressed the matter of actual social responsibility performance, in addition to disclosure, this paper does not examine performance. Furthermore, press release activity is only one type of strategic posture. Future work that employs some other measure may yield additional insight into the decision‐making process. Originality/value Prior study of Ullmann's work has not considered the interactive impact of profit and strategic posture. Furthermore, the actual nature of the disclosure, voluntary versus mandatory, has not been specifically examined. This paper addresses both of these issues.
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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".