Corporate Law and Sustainability from the Next Generation of Lawyers
Bibliographic record
Abstract
Millennials have come of age in an era when environmental and social crises have defined much of their adult lives, as has the recurrent message that time is of the essence. Future generations will bear the greatest burden created by climate change, pandemics, and inequality, but often they are not in positions of power to make impactful decisions about it.This book gives voice to young lawyers offering new critical perspectives in the burgeoning field of corporate law and sustainability. Climate change is an intergenerational crisis, and the solutions and path forward must include intergenerational voices. Millennials are rising in power at a critical juncture in our climate and corporate history, and their perspectives stand apart from those who have been trained into myopic views of what constitutes change. These essays challenge the status quo across a number of pressing topics, including executive compensation, board diversity, decolonialization, crowdfunding, social media risk, corporate lobbying, shareholder activism, tax avoidance, global supply chain management, and human rights, written with a level of thoughtfulness and urgency that demands attention from policymakers and scholars alike.Edited by Carol Liao, a leading expert in the field, and with a foreword by author and filmmaker of The Corporation and The New Corporation Joel Bakan, this book offers timeless research from a diverse group of young lawyers calling for bona fide corporate accountability within legal and regulatory frameworks, including innovative ideas for reform. [From Corporate Law and Sustainability from the Next Generation of Lawyers | McGill-Queen’s University Press]
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.014 |
| Scholarly communication | 0.019 | 0.019 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.011 | 0.014 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".