The leading source of labour statistics

Nurses and midwives: overworked, underpaid, undervalued?

May marks both International Day of the Midwife and International Nurses Day – two groups of workers that play essential roles in any healthcare system. However, both professions – which are dominated by women – are characterised by long hours and low pay. So, what can be done to improve working conditions and help nurses and midwives deliver the best quality care to patients?

ILO data highlights need for disability disaggregated labour force surveys and investment in data systems

Data on labour market disparities between persons with and without disabilities are essential to inform transformative policymaking and programming. Yet, analysis of ILOSTAT datasets reveal that many countries do not collect population-level data on disability status, hampering efforts to disaggregate labour market indicators. Investment in national data systems is needed to advance disability inclusion. This blog focuses on Africa, where we see progress toward more inclusive data systems in many countries, but gaps remain.

Assessing the current state of the global labour market: implications for achieving the Global Goals

The Sustainable Development Goals (SDGs) are a set of 17 global goals to end poverty, protect the planet, and ensure prosperity for all. But with the COVID-19 pandemic upending the global labour market in recent years, progress towards achieving these goals has been disrupted. From rising unemployment and informal work to slowing productivity growth and persistent gender inequalities, the pandemic has highlighted the need for urgent action to build a more resilient and equitable world of work.

Worker and sector profiles (PROFILES database)

Concise description of concepts and definitions, uses, sources and limitations of indicators in the Worker and Sector Profiles, including definitions for the groups of occupations and/or sectors recombined to create these profiles.

Breaking the bias for better gender data

Generating high quality statistics relies on eliminating gender bias at all stages of the production process. This blog looks at how gender bias occurs in statistics and what the ILO is doing to support efforts to minimize it.

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