“The incidence and intensity of poverty are more important in determining poverty based on income alone.” In this context, analyse the latest United Nations Multidimensional Poverty Index Report.

Key learnings from their answer

• ›On Q18 (multidimensional poverty) she made the trend measurable: a bar chart tracking MPI falling ~55% -> ~27% -> 14.6% across the 2005-06 / 2015-16 / 2021-22 rounds, plus a hand-drawn India map to show regional disparity. -> Convert a 'discuss poverty/development' answer into a quantified trajectory (cite the actual numbers across survey rounds) and add a spatial layer for disparity, rather than describing decline with adjectives.
• ›Visually rich: cloud-bubble call-outs, flow/tree charts, an India map, a BRICS world map, an MPI bar chart and a court-pendency pyramid.

Key learnings from their answer

• ›Diagrams are integrated as analysis, not decoration: a Q15 'Deprivation' mind-map splitting Extent vs Source (caste/class/regional/gender) vs Complexity that feeds into 'Informed policymaking', a Q8 bar chart plotting the actual NSS-2017 42/15/24 digital-divide numbers, and a hand-drawn Indo-Pacific map in Q20. -> Make each visual do argumentative work, a labelled chart that carries your own data or a mind-map that classifies causes adds value, whereas a generic box-and-arrow does not.
• ›His Q8 (social infrastructure) is a stat barrage with sources attached, not vague claims: UNICEF 69% under-5 deaths, 40% of higher-ed institutes unaccredited, urban PHCs ~1/7th of rural, NSS-2017 digital divide (42% urban / 15% rural / 24% India), India losing ~1% of GDP to air pollution, social expenditure at 1.2%. -> Build a small bank of figures-with-source for your core themes so a body paragraph reads as evidence, not opinion, and always tag the source (UNICEF, NSS-2017) to make the number land.