The impact of the economic crisis on the situation of women and men and on gender equality policies
Bibliographic record
Abstract
Europe is experiencing a financial and economic crisis. This began with the 'credit crunch' in the financial services sector and evolved as a sovereign debt crisis. Fiscal consolidation and austerity measures have been deployed in response to the crisis to reduce public deficits and debt. This crisis is still unfolding so that the analysis and findings of this report must remain a work in progress. This report aims to assess the impact of this crisis on the situation of women and men in Europe and on gender equality policies. This is important as economic crises are deeply gendered. Past experience cannot provide sufficient insight into the gender impact of this crisis as the position of women has changed considerably since the last major recession. This crisis offers opportunities for radical change, including a potential to advance equality for women and men. However, the crisis also poses challenges where gender equality may be seen as an issue only for the good times. This report is a product of the EGGE and the EGGSI expert networks of the European Commission. It covers 27 Member States, the EEA-EFTA countries and three candidate countries: Turkey, Croatia and FYROM. The core reference period for analysis of the labour market impact is the (nearly) four years between the second quarter of 2008 (when the crisis technically started for the EU as a whole) and the first quarter of 2012 (the latest quarter for which Eurostat data is available at the time of writing. Analysis of the social impact extends over the period between 2005 and 2010.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".