1. STEM gender gap—underrepresentation in engineering and computing, stagnant female participation, persistent gendered subject divide, minor fluctuations 2. Representativeness in large-scale studies—ethnic diversity inclusion, proportional sample accuracy, generalisability of findings, bias minimisation 3. Quantitative gender data—pattern visibility, comparative clarity, statistical objectivity, policy relevance, large-scale reliability 4. Longitudinal method advantages—change over time tracking, recession impact analysis, unemployment persistence, ethnic labour market disadvantage, deep causal insights 5. Age-based work opportunity—youth inexperience barriers, age discrimination, career progression limits, retirement age impact, training access inequality 6. Marxist class theory relevance—economic exploitation, class polarisation, capitalist system critique, growing wealth gap, proletarianisation, neo-Marxist updates