Exploring Diversity, Equality, and Inclusion in South Asian Organizations
Bibliographic record
Abstract
Global shifts in the geopolitical, environmental, demographic, and technological landscape are introducing unprecedented levels of uncertainty into labor markets and employment relations. This unprecedented global shift also demands greater attention to organizations' diversity, equity, and inclusion (DEI) practices. Research on DEI practices has been conducted primarily on mono- cultural Western-oriented or “WEIRD” (i.e., Western, Educated, Industrialized, Rich, & Democratic; Henrich, 2021) countries (Nishi & ?zbilgin, 2007; Rad, Martingano, and Ginges, 2018). However, legislative frameworks, political, societal, religious, cultural, and governance factors have produced DEI practices that vary from country to country and often differ markedly from those in the West (?zbilgin & Syed, 2010; Klarsfeld, Knappert, Kornau, Ng, & Ngunjiri, 2022). Countries in the South Asian region—Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, and Sri Lanka—are multicultural developing economies that are home to one-fourth of world’s population and vary widely in terms of education, democracy, and degree of industrialization (Worldometers, 2025). However, despite the growing importance of this region to the global economy (IMF, 2019), there is a lack of research into the nuances of DEI and attendant practices and policies of South Asian organizations (Saifuddin, Chhina, & Zaman, 2022; Syed & Pio, 2013). This presenter symposium offers novel perspectives to advance management research and practice in a non- Western context by unpacking the causes of inequality in South Asia and how these influence organizational policies and individual actions to create differential career outcomes for underrepresented groups. Overall, the proposed symposium will bring together scholars from DEI, human resources (HR), international management (IM), and social issues in management (SIM) researching diversity and equality in South Asia to present their work and engage in a critical discussion to drive evidence-based DEI scholarship, policies, and programs. Diversity, Equity, & Inclusion in Business in South Asia Organizations Author: Samina M. Saifuddin; Morgan State University Author: Rana Haq; Laurentian University Author: Ravi S. Ramani; Morgan State University Author: Isis Olimpia Gutierrez Martinez; Universidad de las Américas Puebla Diversity Practices in Public vs. Private Organizations in India: Critique of Caste-Blind Practices Author: Poonam Barhoi; Institute of Rural Management Anand Author: Manan Tusharkumar Pathak; UPES School of Business Asynchronous Workflows: Investigating Temporal Diversity Author: Shareefa T P; Indian Institute of Technology, Madras Author: Lata Dyaram; Indian Institute of Technology, Madras Clicks to Connections: Exploring Networking Behavior, Social-Media, & Career Benefits in Bangladesh Author: Samina M. Saifuddin; Morgan State University Author: Laila Zaman; East West University Effect of Cultural Differences and DEI Leadership Effectiveness Author: Harinder Chhina; Carleton University Author: Samina M. Saifuddin; Morgan State University
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.014 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".