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PARTICULAR
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Page No.
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Disclosure and Dissent in India and the United States: Resolution-level evidence from mutual fund voting
Muhammed Zameel K M
DOI:18.A003.ijmra.2026.J1501.10.28304
Abstract:
Indian and United States mutual funds publish how they vote, but their disclosure regimes answer different questions. The study compared the regimes and asked what published statistics can say about dissent, a
recorded vote against a resolution. Regulatory instruments were compared on who discloses, the unit of disclosure, timing, scope and reasons for votes.
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01-11
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Cardiovascular Health and Longevity: Assessing the Burden and Life Expectancy Among India’s Elderly
Dr Anjana A
DOI:18.A003.ijmra.2026.J1501.10.28305
Abstract:
Cardiovascular diseases (CVDs) remain a major contributor to morbidity and mortality worldwide, with their impact increasingly felt in low- and middle-income nations such as India. This study explores the prevalence of CVDs and estimates the life expectancy free from these conditions among elders in India, drawing on data from the Longitudinal
Ageing Study in India (LASI) Wave 1 (2017–18).
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12-23
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Measuring Care Beyond Cure: Outcome Measures in Community-Based Rehabilitation for People Affected by Leprosy
Karen Sahdev
DOI:18.A003.ijmra.2026.J1501.10.28306
Abstract:
Leprosy is curable, yet nerve impairment, wounds, activity limitations, stigma, psychological distress and loss of livelihood can continue after multidrug therapy. Community-based rehabilitation seeks to address these wider consequences, but programmes do not always define or measure success in the same way.
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24-31
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Algorithmic Bias in Recruitment: Examining Artificial Intelligence and Women’s Right to Equal Employment
Afzal Ahamad , Prof. (Dr) Syed Mehartaj Begum
DOI:18.A003.ijmra.2026.J1501.10.28307
Abstract:
The increasing use of artificial intelligence (AI) in recruitment has raised concerns regarding algorithmic bias, gender discrimination, and women’s right to equal employment. This study examines the relationships between AI-enabled recruitment practices, perceived AI discrimination, recruitment fairness, and anti-discrimination policies.
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32-49
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