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Record W4281610360 · doi:10.1177/10564926221103480

We Are Boiling: Management Scholars Speaking Out on COVID-19 and Social Justice

2022· article· en· W4281610360 on OpenAlexaff
Ana María Peredo, Samer Abdelnour, Paul S. Adler, Subhabrata Bobby Banerjee, Hari Bapuji, Marta Β. Calás, Ekaterina Chertkovskaya, Rick Colbourne, Alessia Contu, Andrew Crane, Michelle Evans, Paul M. Hirsch, Arturo E. Osorio, Banu Özkazanç‐Pan, Linda Smircich, Gabriel Weber

Bibliographic record

VenueJournal of Management Inquiry · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsCarleton UniversityUniversity of VictoriaUniversity of Ottawa
Fundersnot available
KeywordsInjusticeRacismIdeologySociologySocial injusticeFace (sociological concept)Environmental ethicsCoronavirus disease 2019 (COVID-19)InequalityPolitical scienceCriminologySocial scienceGender studiesPoliticsLaw

Abstract

fetched live from OpenAlex

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.658
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.073
GPT teacher head0.301
Teacher spread0.228 · 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.

Study designNot applicable
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

Citations18
Published2022
Admission routes1
Has abstractyes

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