Chapter 2: Conceptual Clarifications on Gender Equality and Gender-Responsive Data Analysis
Source: Heise (1994).
57. A gendered life course approach considers that disparities may become more pronounced or attenuated and even reversed in direction as the life cycle progresses. While there may not be major differences for girls and boys in education in Early Childhood, as a child ages and becomes a young adult, any minor differences become more and more apparent. UNICEF (2007) reports in the State of the World’s Children that while the gap between girls’ and boys’ enrolment in primary school has been declining, nearly 20 per cent of girls will drop out of primary school by level 5. Thus, for every 100 boys out of school, 115 girls are in the same situation, and 43 per cent of girls are at the appropriate grade level for their age. Gender parity in primary enrolment does not carry over into parity in secondary school and overall educational attainment. Indeed, by the time these girls reach adulthood, as women they will comprise two-thirds of the world’s illiterate population.
58. Being cross-sectional in scope, census data present a methodological challenge for the life course approach, which generally uses longitudinal survey data of persons’ social, cultural and structural contexts. However, using US census data Stevens (1990) creates synthetic cohorts from the same census year (i.e. computing mean educational attainment for women and men by specific age groups, 20-29 year olds, 30-39 year olds, 40-40 year olds, etc. to know if educational attainment is increasing or decreasing over time for women and men), and Fussell and Furstenberg (2002) follow American cohorts over time using census data gathered at 10-year increments. This method of following cohorts over time is limited in use for countries with irregular census data collections or where question wording has changed. Overall, these cohort construction methods work for some research questions and not others.
MEMORY CARD: SUMMARY PART 1
59. In summary, gender and census data are linked in many ways: Gender advocates need robust and reliable data to sustain their claims and produce more convincing advocacy materials. Data producers need to understand gender issues to make sure the data they generate is fully representative of the entire population, including of vulnerable women such as widows and disabled girls, and of the entire spectrum of issues pertaining to both sexes. Census data has many limitations as a basis for gender analysis, many of which are linked to its focus on breadth (full geographical coverage) rather than depth (few questions). The following chapters will discuss gender issues that can nevertheless be analysed with census data.
Figure 1: Gender Equality: Normative Ideal and Development Objective
(Source: DLPI, Course 3, module 3)
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