A data ecosystem approach

Assessing national status vis-à-vis SDG Target 8.7

This paper outlines an “ecosystem approach” to child labour data collection with this aim in mind. It relates principally to countries that have achieved low levels of child labour and want to monitor and sustain this achievement and to complete the “last mile” towards ending child labour in all its forms.

With the adoption of the Sustainable Development Goals (SDGs), the international community has committed to ending child labour in all its forms by 2025 (SDG Target 8.7). As this ambitious target date is fast approaching, and a number of countries have expressed the intention or aim of achieving SDG Target 8.7 relating to child labour, either nationally, sub-nationally or within a specific sector, there is critical need for strategies on how status vis-à-vis SDG Target 8.7 can be measured, monitored and assessed.

This discussion paper outlines an “ecosystem approach” to child labour data collection with this aim in mind. It relates principally to countries that have achieved low levels of child labour and want to monitor and sustain this achievement and to complete the “last mile” towards ending child labour in all its forms.

However, the approach discussed is also seen as being of relevance to broader country-level SDG Target 8.7 reporting and monitoring efforts, and to wider national efforts towards more targeted and tailored responses to child labour.

The discussion paper is structured as follows. Section 1 details the core indicators for tracking progress towards SDG Target 8.7. Section 2 presents the traditional statistical tools for measuring and monitoring child labour. Section 3 discusses the strengths and limitations of household-based population surveys as a tool for monitoring and measuring child labour in low child labour prevalence contexts. Section 4 looks at how administrative data can be leveraged to complement population surveys in monitoring child labour, tracking child labour warning signs and in informing indicators of child labour risk. Section 5 explores other data collection instruments and analytical tools of potential relevance in this regard. Section 6 concludes.

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  • ISBN Web PDF: 978-92-2-040866-7

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