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The study primarily analysed two dimensions of the goal K.1: the participation of women in climate-related decision-making at the national, European and international level, as well as the share of women in related scientific and technical fields.
In addition, it also examined the available data and information on gender and climate/energy/transport from the 27 member states of the EU, considering how this is integrated in the development and implementation of the related policies in the domestic context.

The availability of information leaves a great deal to be desired. Sound research findings are rare, which doesn’t hide the information provided by certain gender-disaggregated data, e.g. on the distribution of care work, car ownership or meat consumption. The most readily available data were from population surveys on climate change, the energy transition, consumption patterns, etc. Yet given that the difference between statements made in surveys and actual behaviour is considerable, it is only possible to identify tendencies at this stage.

The debates on justice in conjunction with climate policies have thrown the doors wide open for a topic that for a long while was underrepresented in climate negotiations: gender justice*. This is seen in the growing numbers of organizations that have taken up the topics of gender and climate and is demonstrated by numerous papers and articles. What is often missing – both in the organizations and in the papers – is a fundamental theoretical analysis that can be used as the basis for handling the perspectives of gender justice.
The Working Group ‘Women’ in the German NGO Forum on Environment & Development and genanet – focal point gender, environment and sustainability are both organizations located in and active primarily in Germany. They have taken up the challenge and are daring to undertake a first step toward closing this gap. They examine the topic of gender justice and climate in three steps and in three different aspects:

Women are dramatically underrepresented in computer science at all levels in academia and ac- count  for  just  15%  of  tenure-track  faculty.   Understanding  the  causes  of  this  gender  imbalance would  inform  both  policies  intended  to  rectify  it  and  employment  decisions  by  departments  and individuals.  Progress in this direction, however, is complicated by the complexity and decentralized nature  of  faculty  hiring  and  the  non-independence  of  hires.   Using  comprehensive  data  on  both hiring outcomes and scholarly productivity for 2659 tenure-track faculty across 205 Ph.D.-granting departments in North America, we investigate the multi-dimensional nature of gender inequality in computer science faculty hiring through a network model of the hiring process.  Overall, we nd that hiring outcomes are most directly a ected by (i) the relative prestige between hiring and placing institutions and (ii) the scholarly productivity of the candidates.  After including these, and other features, the addition of gender did not signi cantly reduce modeling error.  However, gender di er- ences do exist, e.g., in scholarly productivity, postdoctoral training rates, and in career movements up  the  rankings  of  universities,  suggesting  that  the  e ects  of  gender  are  indirectly  incorporated into hiring decisions through gender's covariates.  Furthermore, we nd evidence that more highly ranked departments recruit female faculty at higher than expected rates, which appears to inhibit similar e orts by lower ranked departments.  These ndings illustrate the subtle nature of gender inequality in faculty hiring networks and provide new insights to the underrepresentation of women in computer science.

Solving the Equation: The Variables for Women’s Success in Engineering and Computing asks why there are still so few women in the critical fields of engineering and computing — and explains what we can do to make these fields open to and desirable for all employees.