Final published version, 559 KB, PDF document
Final published version
Licence: CC BY-NC-ND: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
Final published version
Licence: CC BY-NC-ND: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Missing men, missing infertility
T2 - The enactment of sex/gender in surveys in low- and middle-income countries
AU - Fledderjohann, Jasmine
AU - Roberts, Celia Mary
PY - 2019/12/21
Y1 - 2019/12/21
N2 - Although reproduction involves (at least) two sexed bodies, men are often missing from in/fertility research. Surveys such as the widely-used Demographic and Health Surveys (DHS) engage in often unintentional yet highly consequential practices of gendering. Here we identify two processes through which surveys have the potential to render male infertility invisible: defining the population at risk of infertility in an exclusionary way; and designing survey instruments to select out some groups/issues. Compiling information about survey samples and inclusion criteria in the DHS, and combining this with a qualitative examination of instrument design, we identify areas of men’s invisibility across time and place. While inclusion of men in DHS samples has increased over time, some men (e.g. single and divorced, transgender) remain missing in many survey settings. This is problematic from a reproductive justice perspective. Survey results, which both reflect and contribute to men’s invisibility, are widely used as an evidence-base for family and population policies. Moreover, reproductive health services are only made available to those whose reproductive health needs are recognized; men’s exclusion from the reproductive discourse contributes to the stratification of reproduction. Men’s underrepresentation in in/fertility data also reinforces the notion that reproduction is a woman’s domain, and so contributes to a system that places responsibility for reproduction on women. It is vital to explore how gender is enacted or ‘done’ in such research.
AB - Although reproduction involves (at least) two sexed bodies, men are often missing from in/fertility research. Surveys such as the widely-used Demographic and Health Surveys (DHS) engage in often unintentional yet highly consequential practices of gendering. Here we identify two processes through which surveys have the potential to render male infertility invisible: defining the population at risk of infertility in an exclusionary way; and designing survey instruments to select out some groups/issues. Compiling information about survey samples and inclusion criteria in the DHS, and combining this with a qualitative examination of instrument design, we identify areas of men’s invisibility across time and place. While inclusion of men in DHS samples has increased over time, some men (e.g. single and divorced, transgender) remain missing in many survey settings. This is problematic from a reproductive justice perspective. Survey results, which both reflect and contribute to men’s invisibility, are widely used as an evidence-base for family and population policies. Moreover, reproductive health services are only made available to those whose reproductive health needs are recognized; men’s exclusion from the reproductive discourse contributes to the stratification of reproduction. Men’s underrepresentation in in/fertility data also reinforces the notion that reproduction is a woman’s domain, and so contributes to a system that places responsibility for reproduction on women. It is vital to explore how gender is enacted or ‘done’ in such research.
KW - Survey data
KW - masculinity
KW - gender
KW - infertility
KW - population policy
KW - global health
KW - invisibilization
KW - survey design
KW - reproduction
KW - LMICs
U2 - 10.1515/pophzn-2018-0003
DO - 10.1515/pophzn-2018-0003
M3 - Journal article
VL - 15
SP - 66
EP - 87
JO - Population Horizons
JF - Population Horizons
IS - 2
ER -