We Are Boiling: Management Scholars Speaking Out on COVID-19 and Social Justice
Bibliographic record
Abstract
COVID-19 is the most immediate of several crises we face as human beings: crises that expose deeply-rooted matters of social injustice in our societies. Management scholars have not been encouraged to address the role that business, as we conduct it and consider it as scholars, has played in creating the crises and fostering the injustices our crises are laying bare. Contributors to this article draw attention to the way that the pandemic has highlighted long-standing examples of injustice, from inequality to racism, gender, and social discrimination through environmental injustice to migratory workers and modern slaves. They consider the fact that few management scholars have raised their voices in protest, at least partly because of the ideological underpinnings of the discipline, and the fact these need to be challenged.
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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 | 0.017 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.027 | 0.083 |
| Scholarly communication | 0.028 | 0.029 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.019 | 0.029 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".