Corporate Responsibility and Strategic Groups in the Forest‐based Industry: Exploratory Analysis based on the Global Reporting Initiative (GRI) Framework
Bibliographic record
Abstract
ABSTRACT A growing number of large forest industry companies have declared voluntary adoption of Global Reporting Initiative (GRI) guidelines to avoid the lack of verification in reporting and to alleviate current criticisms of corporate responsibility (CR) practices. In this study, we use quantitative multivariate analysis of CR disclosure data (GRI indicators) from 66 forest industry firms. The results from cluster analysis show that 58% of the major companies in forest‐based industries are following what could be called a relatively defensive approach to CR, while companies proactive towards CR represent only a minority of the sample (18%), and one‐quarter of the companies could be classified as being ‘stuck‐in‐the‐middle’ in terms of CR. CR practices are found to run parallel to and beyond core business activities, number of employees, sales, and production in these three strategic groups. However, no strategic group level differences in terms of the location of headquarters or financial performance were found. Copyright © 2011 John Wiley & Sons, Ltd and ERP Environment.
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How this classification was reachedexpand
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 | 0.013 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".