1. WP3 Work plan presentation Partner 5 (Lausanne)
GARCIA meeting, August , Reykjavik
WP3 Work plan presentation Partner 5 (Lausanne)

2. WP3 OVERALL OBJECTIVES
The main objective of this WP is to understand the role of context in structuring the career opportunities for women in academic occupations, in order to elaborate self-tailored actions that consider local and national specificities.
We acknowledge the need to analyse the societal, local and institutional environments of young scientists in terms of the structure of opportunities and constraints offered by various “welfare”, “gender”, “care” and “employment” regimes.

3. WP3 SPECIFIC OBJECTIVES
Macro: Map national welfare, gender, employment and care “regimes” (e.g. education, family formation patterns, employment, child-care, health, equal opportunities, work-life balance) > Show how these structure women’s career opportunities in general;
Meso: Where pertinent, map any local (cultural, ethnic, religious, linguistic, regional, etc.) differences / particularities within these “regimes”;
Sectorial: Identify the extent to which the academic employment sector is congruent with or deviates from these societal and local “regimes”.

4. WP3 SPECIFIC OBJECTIVES (2)
Use this mapping exercise as a back-drop against which results from the other WPs can be analysed;
Disseminate the results from the comparative analysis to stakeholders (national and local policy makers, decision-makers in academia and research, including trade unions and scientific organisations), in order to explain the importance of context & social policy environment in the shaping of women’s (and men’s) academic career patterns and experiences.

5. Most analyses of the gendering of academic careers share some (implicit) assumptions:
That academic careers share similarities (i.e. across countries) in terms of expectations, working patterns, temporal requirements, etc.
i.e. hypothesis of the internationalisation of criteria of “excellence”, irrespective of national context / disciplinary field / local factors
i.e. hypothesis that all academic institutions are “greedy” in the same way / to the same extent
That these academic career expectations always interact in exactly the same way with the specific “gender scripts” of a given national context
i.e. hypothesis of a communality of women’s experiences of the academic career, irrespective of national context / local factors.
We suggest that GARCIA could / should examine these assumptions in more detail, particularly in WP3 and WP6

6. WP3 METHODS
Most of the research carried out in WP3 will be desk-based (secondary data collection + analysis).
The local and sector-level information may also be obtained through expert interviews with key informants (5 max / country).
Agreement from Trento: Partner 5 to prepares a selection of societal-level data, based on the same statistical indicators for each country.
Each partner provides (informed) interpretation and analysis of this data + additional local / sectorial data.

7. Task 3.2. Mapping societal welfare, gender, employment, and care “regimes”
Description of national-level practices and policies, with particular attention men and women aged years (NB. not 25-35, because data not easily available for this age group), in five main domains:
Education policies and practices at the primary, secondary & tertiary levels (including the women’s access to HE and the % of girls in STEM);
Employment and labour market policies and practices (open/fixed-term contracts; full-/part-time employment patterns; dis-/continuous working patterns, etc.);

8. Task 3.2. Mapping societal welfare, gender, employment, and care “regimes”
Family-formation practices and policies (same-sex partnerships, divorce rates, single-parent families, etc.); In fact, not a lot of comparable statistical data available on these themes.
Care policies and practices (including work-life balance issues, child-care, health, etc.);
Equal opportunity / anti-discrimination / diversity policies, including equal pay.
NB: Domain 5 = different format from the others.

9. Task 3.2. Variations to the national “regimes”
Rational:
Some countries are very homogeneous in their social structure, value systems and legislative frameworks, whereas others are marked by differences between linguistic regions, ethnic groups, generations or other significant types of social stratification.
In some countries, employment patterns in HE & Research differ little from those in other labour market sectors, whereas this sector has marked particularities elsewhere.

10. Task Variations to the national “regimes”
To enable partners to highlight any significant regional / local deviations in relation to the five key policy domains at the national level.
To enable those partners to highlight any policy initiatives that are specific to the HE&R sector in their national context.
The aim here is to identify policies / best practises to encourage the participation of women in science within each national / regional / local context, but which may not appear in the national data or statistics.

11. D.3.3. Cross-national comparison of the countries involved in the project
Based on the national reports (due January 2015), the WP leader will carry out a cross-national comparative analysis of the situation in the partner countries.
Results from the WP3 national and comparative reports will be available as an analytical framework for the other work packages.
A powerpoint presentation of the main similarities / differences between the partner countries will be elaborated, for the collective use of all partners.

12. DELIVERABLES

13. MILESTONES

14. DISCUSSION
Before we move on to discuss the indicators in more details, are there any: QUESTIONS? SUGGESTIONS?

15. DATA COLLECTION GUIDE
For each of the policy domains, the WP3 leader has collated a series of indicators in existing data bases. These are not restricted to Eurostat, because two GARCIA partners (Iceland & Switzerland) are not EU-member states. These data sources include:
(United nations)
More could be made of:
(SHE Figures 2012)

16. EXAMPLES OF INDICATORS FOR EDUCATION
Enrolment ratio at secondary level by sex
Upper and post secondary students by sex
Educational attainment by level of education, age and sex
Graduates by type of programme and sex
Tertiary students by field of study, type of programme and sex
Teachers by level of education and sex
Percentage of population in life-long learning by sex

17. EXAMPLES OF UNECE INDICATORS FOR EMPLOYMENT PATTERNS
Employment rate of persons aged by education and sex
Employment rate by marital status and sex
Employment rate of persons aged by number of children aged under 17 and sex
Employment rate of persons aged by age of youngest child and sex
Unemployment by age and sex
Long term unemployment by sex

18. EXAMPLES OF UNECE INDICATORS FOR EMPLOYMENT PATTERNS
Economically inactive population by reason for inactivity, age and sex
Employment by public and private sector, and sex
Employment by occupation and sex
Employment by education, occupation and sex
Employment by level of education, occupation and sex
Employment by status in employment and sex
Employment by full-time and part-time status, sex

19. EXAMPLES OF UNECE INDICATORS FOR WORK-LIFE BALANCE
Time spent by men and women in domestic activities
Working-time arrangements of couples aged years, by family circumstance and age of youngest child
Time spent in unpaid, paid and total work, by sex
Women’s share of inactive population aged 25-49, by reason for inactivity
Distribution of male and female inactive population aged years, by reason for inactivity

20. EXAMPLES OF UNECE INDICATORS FOR FAMILY-FORMATION PATTERNS
Total fertility rate
Mean age of women at birth of first child
Length of maternity, paternity and parental leave
Paid maternity leave benefits (% of wages covered during leave period)
Enrolement rate of children aged under 3 years in childcare facilities
Healthy life-expectancy, in years at birth.

21. THE UNECE DATA BASE ALLOWS US TO ADOPT A HISTORICAL PERSPECTIVE
Although there are a lot of missing data for the earlier years, the data base enables a breakdown for the following years:
1980
1990
1995
2000
2001; 2002; 2003; 2004; 2005; 2006; 2007; 2008; 2009; 2010
Some data beyond 2011…
We have adopted a temporal perspective for a selection of the indicators. Because of this, some of the Tables are rather unwieldy…

22. Each Regional & local report provides:
On the basis of their in-depth knowledge of their own country context, each partner offers additional data (+ analysis) on any of the chosen indicators when there is known to be significant intra-national variation on that theme (e.g. By linguistic region, nationality, ethnic origin, religion, etc.).
Highlight any significant regional / local / cultural deviations to the five key policy domains at the national level.

23. Each Regional & local report provides:
Partners should also highlight any policy initiatives / practices that are specific to the HE&R sector in their national context.
The aim here is to identify policies / practises to encourage the participation of women in science within each national / regional / local context, but which may not appear in the national data or statistics;
Guiding hypothesis: In countries with limited equality / diversity policies or work-life balance measures at the national / regional level, the HE&R sector may represent an exception.

24. Each Regional & local report provides:
Approx. 1-2 pages of contextual analysis of the data provided for their own country (bibliography based)
Approx. 2-3 pages of comments & analysis on the data relating to each of the first 4 domains. Highlight insights from the comparative perspective;
Approx. 10 pages for the national & local Equal opportunity policy reports (see guidelines for Domain V);
Maximum 5 pages of additional data.
In all, each report = Approx. 25 pages

25. Thank you for your attention…. Comments more than welcome….