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Record W4391401481 · doi:10.1111/1911-3838.12353

Shadows on Solar: A Teaching Case on the Role of Corporate Governance in Addressing Forced Labor Concerns*

2024· article· en· W4391401481 on OpenAlexvenueaboutno aff
Nava Cohen, Lukas J. Helikum

Bibliographic record

VenueAccounting Perspectives · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Geopolitics and Ethnography
Canadian institutionsnot available
Fundersnot available
KeywordsCorporate governanceTransparency (behavior)Multinational corporationShareholderBusinessAccountabilityChinaAccountingPublic relationsStakeholderCorporate social responsibilityBest practicePolitical scienceLawFinance

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.722
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.039
GPT teacher head0.331
Teacher spread0.292 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2024
Admission routes2
Has abstractyes

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