Methodical Snark critical reflections on how we measure and assess civic tech

Measuring women’s empowerment: pushing composite indicator frameworks on projects?

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While the framework remains unchanged, the characteristics and indicators that make up the index change from context to context, aiming to capture the characteristics of an ‘empowered woman’ in the socio-economic context of analysis. The index provides a concise, but comprehensive, measure of women’s empowerment, while also allowing breakdown of the analysis by level of change or the individual indicator.

That’s a description from the launch of Oxfam’s new ‘How To’ Guide to Measuring Women’s Empowerment. This is essentially a manageable algorithm, into which program staff can plug their data into in order to receive a single number representing a complex phenomenon. And while that makes a certain amount of principled sense (we’re all big fans of bespoke measurement approaches), it raises some questions too.

Why, for example, do projects need a single composite number for something as complex as women’s empowerment? There’s measurement approaches designed to feed directly into adaptive management, so that your measurement can improve your practice as you go. This doesn’t seem to be one of them. Hard to see how that single number is going to provide much leverage with donors or stakeholders without lengthy explanation.

This approach also seems to presuppose MEL power users. The guide is concise, and doesn’t give much guidance on how to define or generate the bespoke data that will feed into the composite indicator. It spends just 330 words describing “Step 2: Questionnaire design and defining indicators.” That’s not a lot of how-to for something as complicated as women’s empowerment. It means that this Guide is likely useful to teams that already have stats capacity or strong MEL divisions, but might just be confusing for those that don’t.

So while this approach is likely useful for challenging and improving practice in comparative analysis, the users it anticipates seem like an awkward fit.

Would love to hear anecdotes that show otherwise.

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Methodical Snark critical reflections on how we measure and assess civic tech

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