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Record W1562545698

Towards a Race and Gender-Conscious Conception of the Firm: Canadian Corporate Governance, Law and Diversity

2009· article· en· W1562545698 on OpenAlexaffabout
Aaron A. Dhir

Bibliographic record

VenueSSRN Electronic Journal · 2009
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Governance and Law
Canadian institutionsYork University
Fundersnot available
KeywordsCorporate governanceCorporate lawCorporationSociologyPolitical scienceLawManagementEconomics
DOInot available

Abstract

fetched live from OpenAlex

Recent scholarship in law and corporate governance has focused on the board of directors as a site of inquiry and noted a shift in the board's animating philosophy. It is argued the board's role is evolving from that of a passive stamp of acquiescence to an agent of reform. The current emphasis on the board raises a foundational question. In the context of a globally competitive marketplace and the transnational knowledge society, what are the appropriate characteristics of a corporate director? And more pointedly, has the dominant normative discourse surrounding this question resulted in an exclusionary cultural monolith? Has it served to preserve existing status hierarchies/structures of identity privilege? This paper explores the intersections of Canadian corporate law/governance and race/gender. Part II illustrates the governance landscape in Canada vis-a-vis statistics on corporate board composition. In doing so, a culture of widespread homogeneity is revealed. Following this, I offer possible rationales for the figures with reference to the so-called "pool problem" and issues of implicit cognitive bias. With respect to the latter, I rely on psychological science literature in an attempt to explicate the cognitive processes and structures that inform corporate decision-making. Drawing on available identity narratives, I then consider how unconscious discrimination manifests itself in the everyday lives of subordinated groups within the corporation. In this section, I explore aspects of organizational socialization and the spaces in which identity-formation takes place. Part III examines attempts by commentators to cast board diversification in terms of organizational performance, in other words, the argument that a heterogeneous board correlates to a more profitable, value-generating business. I review the literature in order to establish whether this claim can, in fact, be empirically established. To the extent that it can, I suggest Canadian corporations may actually be perpetuating corporate cultures that stifle factors which might otherwise enable them to successfully leverage diversity. Further, while I acknowledge the market-based approach has value and is attractive as a political strategy, I also express reservations and contend that it should be employed with caution. In Part IV, I canvass potential avenues for reform. Most importantly, I argue that aspects of the legal culture and practice that shape corporate activity should be revisited. The current system - as it relates to the director nomination process, shareholder proposals and existing governance principles - may ultimately serve to facilitate board homogeneity and to undermine future diversification initiatives. In Part V, I delineate four underexplored areas for future research and offer concluding remarks. I suggest that issues of board composition should be of concern not just to those who are preoccupied with corporate governance, but also to those who are concerned by the human rights-related impacts of Canadian transnational corporate activity.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.791
Threshold uncertainty score0.918

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0400.031
Scholarly communication0.0130.004
Open science0.0020.004
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0040.000

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 head0.016
GPT teacher head0.195
Teacher spread0.179 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations8
Published2009
Admission routes2
Has abstractyes

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