Reading a Border Province's Population Pyramid
A provincial planning office in eastern Afghanistan has the following data for its population of 900,000: 47% are under 15; 3% are over 65; the dependency ratio is high; 62% of the population is rural; the literacy rate is 31% overall and 18% among rural women; and only 41% of girls of secondary age are enrolled. The province receives a development grant and must choose between (a) building two new secondary schools for boys, (b) funding girls' secondary schooling with transport and female teachers, or (c) building a vocational training centre for adults. The grant covers only one option.
1. Using the data, explain which option best matches the province's demographic profile, and identify what the data do not tell you.
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The profile is a very young, largely rural population: 47% under 15 means nearly half the population is of school age or younger, and the old-age share is tiny (3%). The high dependency ratio means the working-age group is small relative to children, so investment that raises the productivity of the next generation has the largest long-run effect.
Option (b) matches the data most directly. The weakest measured indicator is rural female enrolment (41% of secondary-age girls) combined with very low rural female literacy (18%). The barriers named in the option, transport and female teachers, are exactly the constraints that rural distance and staffing would create. Option (a) adds capacity where the gap is smaller. Option (c) targets adults, but the adult cohort is small relative to the child cohort, so its reach is limited.
What the data do not tell you: whether the 41% figure reflects supply (no school) or demand (cost, distance, safety), whether there are female teachers available to hire, and whether the grant is recurring or one-off. Those unknowns should be checked before committing.
2. A local elder argues that boys' schooling should come first because boys will be the earners. How should the planner respond using the data?
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The planner should accept the premise that earnings matter and then test it against the numbers. With 47% of the population under 15 and only 3% over 65, the province's future workforce is the whole child cohort, not the boys alone. Excluding half of that cohort from secondary schooling caps the province's future skilled workforce at roughly half its potential, which is a poor return on a one-off grant.
The data also show where the marginal gain is largest. Girls' secondary enrolment at 41% is far below any plausible ceiling, while boys' enrolment is not reported as a crisis. A grant spent where the gap is widest buys more additional enrolment per unit of money.
The response should be respectful and evidence-based: agree that earning matters, show that the demographic structure makes girls' education a workforce investment rather than a welfare one, and propose that the elder help identify the practical barriers (distance, safety, female teachers) so the programme is designed with community support rather than against it.