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Enregistrement W4385222398 · doi:10.5465/amproc.2023.15427symposium

Firms, Occupations, and Markets as Tools for Combating Systemic Racism: Challenges and Opportunities

2023· article· en· W4385222398 sur OpenAlexaboutno aff
Summer Jackson, Vic Marsh, Ray Reagans, Ezra W. Zuckerman, Adia Harvey Wingfield, John M. Robinson, Orlando Patterson

Notice bibliographique

RevueAcademy of Management Proceedings · 2023
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueGender Diversity and Inequality
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPagerRacismSociologyWritRacializationCriminologyPublic relationsLaw and economicsLawPolitical scienceGender studiesRace (biology)

Résumé

récupéré en direct d'OpenAlex

Can for-profit firms, occupations, and markets be part of the solution to systemic racism rather than part of the problem? Past research provides considerable reason for doubt. After all, there is voluminous evidence of racial bias in the allocation of opportunities for employment and career advancement (Fernandez & Fernandez-Mateo, 2006; Pager, 2003; Pager, Bonikowski, & Western, 2009; Pager & Pedulla, 2015; Pedulla & Pager, 2019). Moreover, in Ray’s (2019) influential theory of “racialized organizations,” he argues persuasively that (American) racist schemas have become embedded in organizational rules, routines, and structures. It is in organizations (not via ambient logics alone) that schemas are fused with resource-richness. While social forces act upon the organizations (“racial superstructures”), the reverse path is also well-trod: organizations’ resources enable reinforcement of racist schemas in their own fields, markets, and wider classes, and in society writ-large - systemically (Bonilla-Silva, 1997, 2001; cf., Omi & Winant, 2014; Wilson, 1976, 1987). Ray’s (2019) diagnosis does not deny that organizations change (for good or ill) at certain times, the underlying racist schemas “remain largely stable.” For would-be reformers of for-profit firms, occupations, and markets, this account is daunting because it is a theory emphasizing major stability (amidst minor moves and counter- moves by reformers). For major change ambitions, this implies that organizations should either de-racialize or disband altogether. Yet de-racialization seems impossible given that any cultural expression in an historically racist society—including those by which organizational “spaces” are constructed—are necessarily racialized (Anderson, 2015; 2022). The recognition that it is impossible for firms to de-racialize implies that we should seek alternatives to firms. But it is notable that neither Ray (2019) nor the scholarly publications extending the theory has proposed alternatives to formal organizations as a way to better combat systemic racism. This stands to reason. Research by organizational sociologists and management theorists are unified in noting that while informal groups and networks can achieve remarkable feats of coordination and cooperation over the short term (e.g., Majchrzak, Jarvenpaa, & Hollingshead, 2007; Mollick & Kuppuswamy, 2014; Quarantelli & Dynes, 1977; Wachtendorf, 2004), however, the disquieting potential for informal groups and networks to further systemic racism exists precisely because it is hard to hold them accountable for their actions (Du Bois, 1926). The hierarchical governance mechanisms that constitute formal organizations are essential for providing the “reliability” and “accountability” for efforts that need to be sustained over time and place and in engagement with interested stakeholders (Freeland & Zuckerman Sivan, 2018; Hannan & Freeman, 1984; cf., King, Felin, & Whetten, 2010; Turco, 2016). The potential for reliability (and especially) accountability has been noted as essential (if difficult to achieve) for mitigating discrimination (Castilla, 2015; Foschi, 1996; Lerner & Tetlock, 1999). Accordingly, insofar as recent trends have witnessed a slowly “vanishing corporation” and the “uberization” of the workplace with the rise of the “gig economy,” scholars have tended to see these trends as worrisome rather than promising from the standpoint of combating (racial) injustice (Schor & Vallas, 2021). In short, accountability is essential for dismantling systemic racism and formal organizations are creatures of accountability. As such, formal organizations have the unique potential—however rarely realized—to become tools for dismantling systemic racism rather than tools for perpetuating it. This symposium showcases recent research projects focused on the social processes of inequality and interrogates the role of firms, occupations, and markets in redressing systemic racism in society. In particular, the presenters are focused on the guiding question of how firms might realize this potential, and what are the opportunities for organization theorists to provide guidance in this regard. An Organizational Dilemma: Dismantling Systemic Racism by Building Stable Racially Integrated Spaces Author: Summer Jackson; Harvard Business School Author: Ray Reagans; MIT Sloan School of Management Author: Ezra Zuckerman; Massachusetts Institute of Technology The Sources of Persistence for (Good) Diversity Programs Author: Vic Marsh; U. of Toronto, Rotman School of Management What's In It For Me? Explaining Millennials' Support for Corporate Diversity and Inclusion Policies Author: Adia Harvey Wingfield; Washington U. in St. Louis Left Behind: Affordable Housing and Communities of Color in Suburban Chicago Author: John Robinson; Princeton U.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,012
score de la tête « metaresearch » (Gemma)0,009
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: Théorique ou conceptuel
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,019
Score d'incertitude au seuil0,065

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0120,009
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0030,002
Études des sciences et des technologies0,0090,047
Communication savante0,0190,027
Science ouverte0,0020,011
Intégrité de la recherche0,0060,006
Charge utile insuffisante (le modèle a refusé de juger)0,0100,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,311
Tête enseignante GPT0,353
Écart entre enseignants0,042 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeThéorique ou conceptuel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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