Shadows on Solar: A Teaching Case on the Role of Corporate Governance in Addressing Forced Labor Concerns*
Bibliographic record
Abstract
Abstract Forced labor continues to affect millions of people in the 21st century and worsened globally between 2016 and 2021. Notwithstanding its importance, the issue receives little attention in contemporary business school seminars. Using the recent case of Canadian Solar Inc., a leading solar energy company, this teaching case explores the role of corporate governance as a means of moving toward meaningful changes in the behavior of large, multinational corporations. The case delves into the allegations that the firm has benefited from forced labor by Uyghur Muslims and other ethnic minorities in China's Xinjiang region, exploring the board of directors' actions and a proxy proposal submitted by shareholders. Through this case, students will gain insights into the importance of robust corporate governance, accountability, and transparency in addressing sensitive issues like forced labor. The case highlights corporate governance best practices for companies to adopt, such as proactive board oversight, risk assessment, and transparency.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.015 | 0.012 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".