(a) What do you understand by 'mixed method'? Discuss its strengths and limitations in social research. (20 marks) (b) Define…

(a) Mixed Methods: Strengths and Limitations

• Meaning: mixed methods research combines quantitative and qualitative data, methods and analysis in one study and integrates them to answer a research question better than either could alone (Tashakkori and Teddlie; Creswell and Plano Clark). Johnson and Onwuegbuzie (2004) called it a "third research paradigm", usually grounded in pragmatism: the question, not a philosophical camp, decides the method.
• Background: Denzin's triangulation (1970): of data, investigators, theories and methods. Classic examples are Jahoda, Lazarsfeld and Zeisel's Marienthal study of an unemployed community (1933), which combined statistics with observation and diaries.

Core designs (Creswell):

• Convergent: quantitative and qualitative data collected together and compared;
• Explanatory sequential: a survey first, then interviews to explain surprising results;
• Exploratory sequential: qualitative work first to build categories, then a survey to test and generalise them.

Strengths:

• Triangulation: agreement across methods raises confidence in findings;
• Complementarity: numbers show how much and how widespread; narratives show why and how;
• Development: qualitative work improves survey questions in local idiom (for example, how people name caste, work or illness);
• Initiation: contradictions between methods can open new questions (Greene, Caracelli and Graham, 1989);
• Breadth with depth: links macro patterns to micro experience, as in Jeffery, Jeffery and Lyon's Labour Pains and Labour Power (1989), which joined a village household census with ethnography of childbearing in western Uttar Pradesh;
• Policy relevance: policymakers want both measurable outcomes and an understanding of implementation.

Limitations:

• Paradigm incommensurability: critics in the "paradigm wars" argue that positivist and interpretive assumptions about reality cannot simply be combined;
• Weak integration: many studies merely place two methods side by side ("bolted on") without real integration (Bryman, 2007);
• Hierarchy: the qualitative part is often reduced to illustrative quotes serving the survey;
• Conflicting findings may be hard to reconcile;
• Cost, time and skill: needs large teams competent in both statistics and fieldwork;
• Reporting difficulties within journal word limits.
• Conclusion: mixed methods is valuable when the research question needs both extent and meaning. Its worth depends on genuine integration and clear reasons for combining methods, not on using both for their own sake.

(b) The Gig Economy, Labour Markets and Social Security

Gig economy: a labour system of short-term, task-based work in which workers are paid per task or "gig", often through digital platforms that match them with customers and manage them through algorithms.

• Platform workers: app-based (ride-hailing, food delivery, home services, online freelancing);
• Non-platform gig workers: casual and own-account workers in conventional sectors;
• India's Code on Social Security, 2020 (in force from 21 November 2025) defines both "gig worker" and "platform worker" as workers outside the traditional employer–employee relationship.
• Scale: NITI Aayog (India's Booming Gig and Platform Economy, 2022) estimated about 77 lakh gig workers in 2020–21, projected to reach about 2.35 crore by 2029–30.

Impact on the labour market:

• Positive:
• low entry barriers and quick income for youth, migrants and those without formal credentials;
• flexibility in hours, useful for students and those with care duties;
• some formalisation through digital payments and records;
• Negative:
• Precarity: insecure, variable earnings and no job security (Guy Standing's precariat);
• Misclassification: calling workers "partners" or independent contractors shifts risks and costs (vehicle, fuel, phone, accidents) onto them;
• Algorithmic control: ratings, automated deactivation and opaque incentive changes give workers little voice, a form of control without the obligations of an employer;
• Long hours and safety risks from delivery-time pressure;
• Segmentation: a well-paid freelance top and a large low-paid base; women face safety concerns and harassment;
• Weak collective voice: workers are dispersed, though unions and associations of app-based workers have organised strikes.

Impact on the social security net:

• gig workers traditionally fell outside EPF, ESI, gratuity, maternity benefit and minimum wage protection, since these depend on an employer;
• Code on Social Security, 2020: schemes for gig and platform workers, funded partly by aggregators' contributions of 1–2% of annual turnover, capped at 5% of what they pay these workers, and a National Social Security Board;
• Union Budget 2025–26: registration on the e-Shram portal, identity cards, and health cover under PM-JAY for platform workers;
• State laws: the Rajasthan Platform Based Gig Workers (Registration and Welfare) Act, 2023 and Karnataka's Platform Based Gig Workers (Social Security and Welfare) Act, 2025 create welfare boards and funds;
• Global comparisons: the UK Supreme Court held Uber drivers to be "workers" (Uber BV v Aslam, 2021), and the EU Platform Work Directive (2024) presumes an employment relationship;
• Gaps: coverage is scheme-based rather than a right, registration and portability are weak, and the Codes do not give gig workers full employment status. The Fairwork India ratings show wide variation in fair pay and conditions across platforms.
• Conclusion: the gig economy creates work without the employment relationship. The challenge is to keep flexibility while building a portable, universal social security floor and algorithmic transparency.

(c) Technology, Automation and Work

Changes in the nature of work:

• Deskilling vs upskilling: Harry Braverman (Labor and Monopoly Capital, 1974) argued that technology separates conception from execution and increases managerial control. Post-Fordist writers (Piore and Sabel, 1984) saw flexible specialisation and skilled, multi-task work;
• Job polarisation: automation replaces routine tasks, both manual and clerical, while demand rises for high-skill analytic work and low-paid, non-routine service work (Autor, Levy and Murnane, 2003). The middle is hollowed out;
• Automate and informate: Shoshana Zuboff (1988) noted that information technology can either replace workers or give them more knowledge; later she warned of surveillance (2019);
• Algorithmic management and remote work blur the boundaries between work and home;
• Hidden labour: "ghost work" (Gray and Suri, 2019), such as data labelling and content moderation, often done in the Global South, including India.

Impact on employment:

• Pessimistic estimates: Frey and Osborne (2013) put about 47% of US jobs at high risk of automation;
• Moderate estimates: OECD (Arntz et al., 2016), assessing tasks rather than whole occupations, found about 9% at high risk;
• Net job churn: the World Economic Forum's Future of Jobs Report 2025 projects about 170 million jobs created and 92 million displaced by 2030;
• Generative AI: the ILO (2023) found that clerical work is most exposed, and women more so, with augmentation more likely than full replacement;
• India: a large informal sector, low wages and weak social protection make displacement harder to absorb, and IT services and back-office jobs face pressure from AI, while new work emerges in the digital and platform economy.

Critical assessment:

• past waves of technology created more jobs than they destroyed, so the "lump of labour" fear is often exaggerated;
• however, the transition costs fall unevenly, on older, less-educated and routine workers;
• technology does not act by itself: institutions such as unions, labour law, skilling and social protection shape whether it degrades or improves work;
• productivity gains often go to capital rather than wages.
• Conclusion: automation mostly transforms work rather than ending it. Its social outcome depends on policy choices about skills, social protection and the share of gains going to workers.