Academic time allocations among Early Career Researchers in Germany and Norway

Paper to be submitted to the STI 2023 conference, Improving scholarly evaluation practices in light of cultural change,
27-29 September, Leiden

Topics: academic careers, equity, diversity and inclusion, science policy, science indicators,

Sabine Wollscheid^*, Kaja Wendt^** and René Krempkow^***

^*sabine.wollscheid@nifu.no

ORCID; ID: https://orcid.org/0000-0001-7376-9820

Nordic Institute for Studies in Research Innovation and Education (NIFU), Norway

^** kaja.wendt@ssb.no

ORCID; ID: https://orcid.org/0000-0002-2430-9067

Statistics Norway, R&D, technology and business development, Norway

^*** rene.krempkow@iu.org

ORCID; ID: https://orcid.org/0009-0000-6760-3285

IU – International University of Applied Sciences Berlin, Research Department, Germany

Abstract (146 words)

In Germany and Norway, there have been vivid discussions about precarious working conditions and challenges to balance work- and private life of Early Career Researchers (ECRs). The focus of this article are ECRs in Germany and Norway. ECRs are here defined as PhD students and postdoctoral researchers. PhD students in Norway are to a higher degree scholarship holders and at the same time employed at higher education institutions than their German counterparts. Germany and Norway differ in their historical approaches facilitating gender equality, even though gender policies are converging in both countries. Drawing on data from the German Science Survey 2019, Time-use survey of Norwegian academic staff at higher education institutions and data from the register of research personal in Norway, we explore time allocation for academic activities among ECRs in Norway and Germany considering different context variables (gender, discipline, citizenship) providing implications for further research.

1. Introduction

Research careers are high on the international agenda. The European Research Area Policy Agenda aims at making research careers more attractive by revising the Charter and code for researchers and launching an observatory on research careers (ReICO) with the OECD in 2024. Important aspects to address are precarious working conditions, gender equality and the promotion of mobility between sectors and countries, in particularly for ECR, denoted the “most vulnerable group in the science system” (Laudel & Glaeser, 2008, p.388).

This paper focuses on ECRs in Germany and Norway with similar discussions about precarious working conditions and challenges in work-life balance. In Germany, e.g., the ongoing discussion was facilitated by the nationwide campaign “#Ich bin Hanna” (Schwägerl, 2021). These discussions have informed the topic, time allocation on academic activities, conceptualised as R&D input indicator (Aksnes et al., 2016), and how much it could be – also related to different welfare regimes – a condition of a healthier academic culture.

Despite distinct changes in academic careers and evaluation systems in Europe, over the last decades (Kwiek, 2019), researchers still identify themselves with their work (Djerasimovic & Villani, 2020). For more “time-privileged” ECRs research can mean a “lifestyle” (Krempkow, 2022). However, ECRs usually face non-permanent contracts and meet obligations of hard work in a highly competitive environment (Wendt et al., 2021). ECRs might be “time and money poor” (Jäckel & Wollscheid, 2007) and highly motivated at the same time (Jacob, 2011). ECRs here comprise PhD students and postdoctoral researchers. Norway and Germany were chosen, showing both similarities and differences in research systems and welfare regimes.

In both countries, higher education institutions have a long tradition of the Humboldtian university. They have followed recommendations of the Bologna Declaration, although to a different pace (Kehm et al., 2010). Characterised by ‘central academic research systems’ (Bégin-Caouette et al., 2016), both countries show relatively high graduation rates at doctoral level. The PhD density in the population is somewhat higher in Germany at 338 awarded doctorates per million habitants in 2021; in Norway there were 310 per million inhabitants in 2023. Over the last decade the PhD density in the population has been decreasing slightly in Germany, while increasing in Norway. PhD students in both systems often work full-time. However, although the Bologna Process has re-enforced a coherent reform of doctoral training, Norway and Germany differ in implementation and organisation of doctoral training (Ambrasat & Tesch, 2017). Its structure and organisation comprise working and employment conditions of ECRs (e.g., Jacob, 2011) embedded in wider academic research systems (Bégin-Caouette et al., 2016).

The two countries differ in their approaches facilitating gender equality. Conservative welfare regimes (Germany) aim at preserving social structures and hierarchies, in particularly traditional gender roles. Socio-democratic welfare regimes (Norway) are characterised by the existence of universal welfare with the aim of de-commodification by treating all citizens equally. (Esping-Andersen, 1990; Pechar & Andres, 2013). Over time, Germany has converged more to the Nordic model. In 2007, the government passed a reform of the parental leave benefit system in line with the Nordic model (Spiess & Wrohlich, 2008).

2. Literature review and working hypothesis

ECR models in Norway and Germany

Doctoral training is regarded as the first stage of an academic career (apprenticeship) (Laudel & Gläser, 2008) with implications for PhD students’ working conditions. Since 2000, as a part of the Bologna process, doctoral training has become included as the third cycle in higher education (Kehm, 2010). Having a doctoral program, universities could demonstrate that they take responsibility for the quality of their doctoral training (Bloch, 2018). However, across Europe there are still significant differences in doctoral training. PhD students differ in access to resources (Waaijer et al, 2016), time allocation on research (Ambrasat & Tesch, 2017), and conditions for an academic career (Laudel & Gläser, 2008).

In Norway doctoral training is embedded in a higher education system regarded to serve the public. Research is largely funded by block grants, divided between performance-based allocation regarding student production, research funding from external resources and research publications (Schmidt, 2007). PhD students contribute to the production of research to a stronger degree than those in other countries. ECRs (junior staff) in Norway spent for example more time on research compared to their counterparts in a couple of other European countries (Teichler, 2014, 72). Also, in 2020/2021 the average share of time spent on R&D is high at 70% (Wendt, et al. 2021). More than 90% of PhD candidates hold a scholarship from a higher education institution (RCN, 2021). They are temporal employed in higher education institutions that implies a regular salary comparable with the entry-level salary for holders of a master’s degree in the public sector (Frølich et al. 2018).

In Germany, doctoral training was not specified until the 2000s, just defined as peculiar right of universities, but at the same time “loosely coupled to the university” (Bloch, 2018, 301). Until the 2000s, PhD students were not enrolled in any structured programme, with the majority employed as research associates, recruited by a professor and not by the university. However, with the Excellence Initiative in 2005 the number of structured doctoral programmes has been increasing. Having a doctoral programme has become the norm. (Bloch, 2018).

There are, however, some country differences. Doctoral training in Germany seems to be more diverse compared to that in Norway distinguishing between five categories of PhD students¹. The largest groups are research assistants (41.2%), followed by scholars (29.10%) and external candidates with a job (16.10%). These groups differ on various dimensions including time resources for work on thesis, closeness to supervisor, integration in scientific community, embeddedness in research producing organisation, motives for scientific career, and degree of structuration and formalisation of training. Scholars score very high on time resources, while external candidates with a job score very low. (Ambrasat & Tesch, 2017).

In Norway, PhD-students are employed in temporary recruitment positions at the higher education sector. In 2021 almost 70% were funded by the institution, while almost 14% were funded by the Research Council of Norway, 7% by a university hospital and 7% hold another scholarship (RCN, 2021, table 7.12).

The second stage of the academic career is characterised by more independence to conduct research but also continuation of non-permanent, precarious working contracts (both countries) (Gunnes et al., 2020 for Norway). In general, the postdoctoral phase can be described as less structured compared to the doctorate (Baader et al., 2017). OECD (2021) has together with the EU for several years addressed research careers and emphasized the need of reforms of postdoctoral training for more diversity, more flexible career paths and to relieve precarity for early-career researchers.

Working hypothesis 1 (H1): We assume that ECRs in Germany are more diverse in terms of time allocation than their more homogeneous counterparts in Norway who are mostly scholarship holders.

Gendered time allocation on academic work

Previous literature has investigated time allocation on academic activities, which can be regarded as an intervening factor for the association between gender and research productivity (Zuccala & Derrick, 2022). Interviewing doctorate degree holders in Iceland, Staub and Rafnsdottier (2020) found that men seemed to feel a higher degree of agency in terms of time management and work-life balance compared to female degree holders even in a country with a high level of gender equality.

Further, in general there has been shown a negative relationship between research productivity and the presence of children, in particularly for women (REF). However, for Norway Kyvik (1990) found that women with (older) children are more productive than those without children and just as productive as men in the same situation (Kyvik & Teigen, 1996). At the same time, there is a relatively low share of female ECRs with children in countries like Germany (Briedis et al., 2021), a conservative welfare regime. The German Scientists Survey 2019 reveals only minor gender differences for time spent on research for parents, while differences were significant for ECRs with and without children (Ambrasat et al., 2022). Given a low share of PhD students with children in Germany (17% in total) (Briedis et al., 2021) and ambiguous findings, for reducing analytical complexity, we skip children here as an independent variable in our analyses of ECRs in Germany and Norway.

Moreover, we assume time allocated to research (input) being positively associated with research output (Manchester & Barbezat, 2013). For gender differences, there is a vast literature on research output, measured by bibliometric indicators (Larivière et al., 2022). Findings are, however, far from consistent. For Norway, Nygaard et al. (2022) show only moderate gender differences in publication activities. Gender differences were strongly reduced after considering age, academic position, and discipline. Comparing researchers in Italy and Norway, Abramo et al. (2022) show large differences in productivity in favour of men, in particularly for the top 10% performing researchers. For assistant professors they found only a small gender gap for Italy, which was even smaller for Norway.

Working hypothesis 2 (H2): We assume to find relatively little gender differences for time allocation on academic activities for ECRs in Germany and Norway. Further, we assume that time allocated on research is positively correlated with research output, measured in number of scientific publications. We will test this hypothesis with the German data in the final paper.

Disciplinary differences in academic work

Disciplines differ in their epistemology and a common distinction is between hard vs. soft disciplines (e.g., Becher and Trowler, 1989). Hard disciplines, including natural sciences, life sciences and engineering, are characterised by an accumulative, highly structured epistemology. Soft disciplines including social sciences and humanities (SSH) are characterised by a non-accumulative and open epistemology.

Working hypothesis 3 (H3): We assume to find relatively small gender differences for time allocation on academic activities for ECRs in Germany and Norway, but larger differences according to discipline.

Differences in research patterns and productivity for citizenship

Scholars have investigated associations between international mobility and research patterns including productivity and impact, with mixed results. A small Norwegian study found that international mobile researchers during their careers published more and were higher cited compared to their less international mobile counterparts (Aksnes et al., 2013).

Working hypothesis 4 (H4): We assume to find differences in time allocated to academic activities and research productivity according to country background which might indicate international mobility. We assume differences in time allocated on research and productivity for ECRs in favour of those with a foreign citizenship indicating mobility.

3. Methods and data

The Scientist Survey is a nationally representative trend study and an important tool for analysing working and research conditions at German universities and higher education institutions with the right to award doctorates. The survey is designed and conducted every three years as a multi-topic survey.² Here, we use data from the most recent survey and from a subsample comprising ECRs. (Ambrasat et al., 2022).

Using time-use survey data among all academic staff at Norwegian higher education institutions in 2020/2021,³ we look at how employees distribute their working hours across different tasks (e.g., teaching, research, supervision), and how much they work each week. In our analyses, we use time-use data for ECRs and demographic variables (e.g., gender, citizenship, discipline).

Table 1: Overview over our data and variables to use

RQ	Germany: DZHW-Scientists Survey 2019	Norway: Time-use survey 2021
Control variables	Gender (female, male) Full-time researcher (40 hours and more)	Gender (female, male) Full-time researcher (40 hours and more)
Independent variables	Independent variables Discipline Pre-doc; Post-doc Citizenship (German Citizenship; non-German)	Independent variables Discipline Pre-doc; Post-doc Citizenship (Norwegian Citizenship vs. non-Norwegian)
Dependent variable (input indicator: time-use for R&D activities)	Dependent variable Working-time (by contract; actual) Time for teaching (by contract; actual) Share of working time on following activities (on average) Research Review Teaching Supervision of students Searching for funding “academic housework”/administration Other tasks Average number of publications (journal publications)	Dependent variable (actual time-use) Time-use for academic activities Teaching Research Supervision Dissemination Administration Other tasks (i.e. professional practice and museum and art activities),

First, we conduct bi-variate analyses (mean differences) including time-use and share of activities (time allocation) and gender, followed by analyses including discipline and citizenship.

Second, we include several independent variables in the model to elaborate more nuanced multi-variate analysis. To elaborate H1, we explore variances in time allocation and construct different categories of ECRs in terms of time restrictions. We conduct analyses for ECRs in different categories (gender, citizenship, discipline).

4. Findings

Table 2 shows that ECRs in Norway and Germany report similar real working hours. The German data, however, show a higher distribution (SD) compared to the Norwegian data.

Table 2: Working hours per week among Norwegian and German PhD students (Mean (SD))

	Norway		Germany
Working hours	PhD students1 (N=1,064)	Postdoctoral researchers (N=262)	PhD students2 (N=2,885)	Postdoctoral Researchers (N=4,216)
Working hours (contract)	-	-	30.3 (9.6)	36.3 (7.9)
Working hours (real)	43.9 (7.6)	44.4 (6.5)	40.0 (10.9)	44.3 (11.5)

¹Source: Norwegian time-use survey 2020/2021.

²Science Survey 2019 (Ambrasat et al., 2022).

Table 3: Time allocation among Norwegian and German ECRs. Share of time in the academic year (%)

	Norway1		Germany
Activity	PhD students	Postdoctoral researchers	PhD students2	Postdoctoral researchers
R&D/ work time for research	70.3	66.8	49.8	36.6
Teaching/ work time for teaching	13.6	12.2	17.2	19.8
Supervision	2.7	7.8	10.9	12.7
Administration1 / Funding acquisition + self-management + Management2	5.6	6.0	12.2	19.5
Dissemination1/ Work evaluation2	4.7	5.6	4.3	6.5
Other	3.1	1.6	5.6	4.9
Total	100	100	100	100

¹Source: Norwegian time-use survey 2020/2021.

²Science Survey 2019 (Ambrasat et al., 2022).

Table 3 indicates that Norwegian PhD students on average spent more time on R&D work, i.e., approximately 70% of their time-budget. In contrast, their German counterparts spend only 49.8% of their time-budget on research. Our findings indicate that ECRs in Germany are more heterogeneous in terms of their time allocation. We have classified four groups of ECRs according to their contractual work time (up to 20 hours; 21 to 30 hours; 31 to 38 hours; 39 hours and more) for further analysis.

Table 4 reveals large differences in time share allocated to research across disciplines and across the two countries. In both countries, PhD students in Life sciences and Natural sciences spent over 60% of their working time on research, while this share is under 50% for those in Germany. PhD students in engineering show the highest share for research, with 75.6%.

Table 4: ECRs across disciplines in Norway and Germany – Share of work time for research – in %, Mean (SD)

	Norway		Germany
	PhD students1 (N=1205)	Post-doctoral researchers (N=283)	PhD students2 (N=2885)	Post doctoral researchers (N=4216)
Social Sciences and Humanities	67.9 (25.0)	62,6 (22,7)	41.3 (25.4)	34.1 (23.3)
Life Sciences (Medical and health sciences for Norway)	73.2 (24.1)	68,7 (25,8)	61.9 (24.9)	38.2 (25.1)
Natural Sciences	70.8 (21.8)	63,1 (24,2)	60.7 (23.4)	41.7 (24.8)
Engineering	75.6 (21.1)	59,7 (29,8)	46.6 (24.2)	31.2 (23.9)
Without classification	-		(45.7) (25.4)	31.2 (22.6)

¹Source: Norwegian time-use survey 2020/2021.

²Science Survey 2019 (Ambrasat et al., 2022).

Table 5 reveals more nuanced findings across discipline and gender.

Table 5: Time allocated on research and teaching for female and male ECRs (working >= 39 hours) across disciplines in Germany (N=4389)

	Male ECRs			Female ECRs
	share of work time research	share of work time teaching	Funding acquisition	share of work time research	share of work time teaching	Funding acquisition
SSH (N=1068)	36.0** (22.6)	24.2** (18.0)	6.0** (8.0)	34.0** (23.1)	27.4** (20.3)	6.3** (8.8)
Life Sciences (N=653)	36.8** (25.0)	14.4** (15.7)	5.9** (7.1)	40.7** (25.2)	12.3** (14.8)	6.4** (9.2)
Natural Sciences (N=833)	43.3** (25.3)	17.8** (16.3)	6.3** (8.1)	44.0** (25.5)	17.4** (19.1)	5.6** (8.3)
Engineering (N=812)	41.0** (25.0)	15.1** (13.8)	9.4** (12.0)	40.0** (23.0)	19.1** (17.0)	7.2** (11.0)
Other (N=94)	36.0** (22.3)	19.0** (20.2)	10.2** (13.4)	31.4** (23.0)	27.4** (22.2)	5.8** (8.5)
Total (N=4389)	39.5** (24.6)	18.0** (16.4)	7.3** (9.7)	38.0** (24.3)	21.0** (19.6)	6.0** (9.0)

**stat.-significant <0.01.

Table 6: Time allocated academic activities for ECRs German citizenship) and non-German citizenship) (N=7034)

	Male: Share of work time on …					Female: Share of work time on …
	Research	Teaching	Funding acquisition	Super-vision	Work evalu-ation	Research	Teaching	Funding acquisition	Supervision	Work evaluation
German citizenship Male (N=3303) Female (N=2540)	40.3** (24.7)	18.9** (17.1)	6.5** (9.4)	12.4** (9.8)	5.6** 6.4)	40.00** (25.9)	20.6** (20.0)	5.0** (8.6)	12.2** (10.0)	5.0** (6.4)
Non-German citizenship Male (N=636) Female (N=483)	55.3** (26.2)	12.2** (16.9)	4.7** (7.8)	10.3** (10.2)	7.6** (8.3)	50.0** (26.8)	16.7** (20.9)	5.5** (8.8)	10.4** (11.0)	6.6** (8.3)
Total	43.0** (25.6)	17.8** (17.3)	6.2** (9.2)	12.0** (9.9)	5.9** (6.8)	41.2** (26.3)	20.0** (20.1)	5.0** (8.6)	11.9** (10.2)	5.2** (6.7)

5. Discussion and implications for further research

We investigated time allocated to academic activities and differences according to gender, discipline, and citizenship. For the future, we plan to elaborate the link between time allocation (input indicator) and research output, captured by bibliometric indicators, such as number of published scientific articles, criteria which might disfavour female ECRs and ECRs with children in evaluation processes.

On the backdrop of ongoing reforms of research assessment in Europe (ARRA) more generally and assessment practices of ECRs more specifically, we might replicate our analyses based on the Fourth Scientist Survey 2022/23 in Germany and comparable data in Norway, investigating relations between several input indicators (e.g., funding, time for research), output indicators and differences according to gender, citizenship, and discipline.

Further, one could focus on specific groups of ECRs, for example those with family obligations. Given a positive association between time allocation on research and research productivity and impact, further analyses could even more shift the perspective on a variety of R&D output indicators, comprising established bibliometric indicators (e.g., Aksnes et al., 2016) and alternative indicators of impact, in line with current reforms of research assessment with a stronger focus on diversity and gender equality in research assessment.

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Open science practices

Data used in the paper are partly openly available. The Science Survey 2019 is freely accessible for the academic community via a Scientific Use File (SUF), after request at the Research Data Centre (fdz.dzhw.eu/en/data-usage).

Further, we plan to publish our article in an open access journal (gold open access or hybrid open access.).

Author contributions

All the three authors have developed the proposal for the article and contributed to writing of the manuscript. SW has outlined a draft, with contributions by KW and RK. For analyses KW has conducted the analyses based on Norwegian data, while SW has conducted the analyses based on the German Researcher Survey with comments by RK.

Competing interests

Authors declare of having no competing interests.

Funding information

This work is funded by Nifu (internal funds).

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1. Except PhD students in medicine, who were not included in the sample. The five groups are: Research assistants, research aids, scholarship holders, external candidates with a job and external candidates without a job.↩︎

2. DZHW Scientists Survey | About the survey↩︎

3. Time-use survey conducted to calculate R&D coefficients for Norwegian R&D statistics conducted every 5 years (Wendt et al. 2021).↩︎