Today is the first day of COP21, and the stakes have never been higher.
It is hoped that these crucial talks will reach a deal to limit the warming of our planet to two degrees Celsius.
In his recent blog, my colleague Damiano Borgogno introduced the Global Support Programme, which was created because “ the technical information presented…is not easy to digest by policy makers and their outreach to the general population is weak.”
In his blog, the Nonprofit Chronicles, Marc Gunther writes:
How do feedback loops differ from conventional monitoring and evaluation (M&E)? One attendee told me that feedback loops are the equivalent of diagnosing and treating a disease; a conventional evaluation is more like an autopsy, and thus of limited value to the patient.
This leads us to our question in Tunisia:
Can info culled from big data help us monitor (read: diagnose and treat) in real-time the achievement of Global Goal 16(read: the patient)?
While researching gender inequalities in labour markets of these countries, I searched for evidence on how the challenge of job creation can be overcome without perpetuating gender inequalities in the region, and preferably, by reducing them.