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Utopian Discourses Across Cultures

Scenarios in Effective Communication to Citizens and Corporations

Edited By Miriam Bait, Marina Brambilla and Valentina Crestani

The term Utopia, coined by Thomas More in 1516, contains an inherent semantic ambiguity: it could be read as eu topos (good place) or ou topos (no place). The authors of this volume analyze this polysemous notion and its fascination for scholars across the centuries, who have developed a variety of visions and ways to explain the «realization» of utopian discourses. The experts in the fields of sociology, political science, economics, computer science, literature and linguistics offer extensive studies about how utopian scenarios are realized in different cultural contexts.

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The Care Factor: A Proposal for Improving Equality in Scientific Careers.

← 156 | 157 →

Giampietro Gobo

The Care Factor:

A Proposal for Improving Equality in Scientific Careers
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“Usually behind every great man there is a great woman; but behind a great woman there is always a great domestic servant.”

–Luciana Littizzetto, comedian

In academia, as in other spheres of work, there exist disparities associated with discrimination based on discipline. In academia, for instance, some research ← 157 | 158 → topics are considered more mainstream than others, and some research methods more relevant than others. Discrimination also happens in terms of ethnicity and gender, etc. For some of these disparities, there is significant reflection literature written on the topic; but other forms of discrimination have come under less critical scrutiny.

An issue not yet sufficiently explored concerns the relationship between care activities and scientific research, particularly the question of how the former could have an impact on the latter. More specifically, how with increasing care-giving we can have a slowdown in scientific output. Moreover, since the latter is one of the main criteria for hiring or promoting a candidate, it becomes especially important to shed light on this relationship.

This correlation does not, at first, pertain to the theme of the genre, but who (man or woman) is engaged in care (both motherhood and fatherhood). In the younger generations, care activities are further balancing out between the genders, albeit slowly, with men assuming greater responsibilities and demands in the domestic sphere.

However, since they still expect women to be more engaged in the care, this correlation is particularly unfavorable to women. For this reason, practical proposals to reduce inequalities in scientific careers are urgently needed.

1.  How is the Scientific Product of an Individual (Currently) Evaluated?

Because publications are an increasingly important criterion for evaluating a candidate who is applying for a job or being considered for a promotion, it is important to carefully analyze the inner mechanisms of the evaluation process. This provides insight into how these evaluative mechanisms tend to discriminate, often unconsciously, against the very people who are most involved in care activities, which (we assume) is the main cause of the slowdown in the production of scientific research. In the following sections, we will analyze this evaluation process.

Measurement?

Usually the “measurement” of the scientific production refers to the output of an individual. In fact, measurement is an evaluative operation allowed only

a. with variables that have continuous properties (e.g. time, weight, height, income, age etc.); and

b. where there is a measurement unit (based on a predetermined amount or size, which is conventionally accepted). ← 158 | 159 →

Only these two requirements, which must both be present, allow for measurement to be used (see Marradi 1981, 1990 for a discussion).

Instead, the evaluation of scientific production rests on other procedures or methods, including counting, classification and reading (the content of a publication). None of these methods, however, are measurements (see Tab. 1).

Tab. 1: Three procedures used in the evaluation of scientific products

CountingClassifying

(not countable)
Reading

(the content of the scientific product)

h-index (based on the number of quotations)

number of publications (above or below the median)

Impact Factor of the journals in which the article was published

number of readers and downloads for a publication

number of tags, bookmarks, comments, tweets or blog posts to assess the impact of authors or publications

the language (preferably English) in which s/he published

if it is books or articles, or chapters (of books)

whether published with editors (in the case of publications on journals)

taxonomy of the journals (top, average, bottom journals, with preference for the top ones…)

taxonomy of publishers (with preference for prestigious ones…)

thorough reading

fast reading

skimming

The contemporary tragedy is that counting and classifying are rapidly replacing reading, which should be the main evaluative method used. In other words, how do I evaluate an article if I have not previously read it? How can I assess the scientific output of an individual if I have not read their work? Bibliometric and classificatory nouvelle vague has invented shortcuts: just a few counts and classifications, and you are done. In this way, two (useful but surely) peripheral modes that do not focus on the content of a publication have now become the main evaluative procedures. This results in a loss of the possibility to evaluate the merit of a publication2. ← 159 | 160 →

The situation is such that evaluators and recruiters are often flooded with an avalanche of publications that must be evaluated in a short time (an oxymoron!) in the midst of all the many other things a scientist has to do. The result is that candidates’ scientific publications are not read closely, except for a few cases, with evaluators only skimming to search for the soundness of scholarship. This is, in short, a humiliating practice for the authors of these publications.

2.  Monitoring or Evaluating?

This reflection on the (current) assessment practices of the scientific research published by a candidate is that perhaps what evaluators and recruiters are doing is not a genuine evaluation, even if the intent is honest. In fact, evaluation should be “a cognitive activity [that] aims to provide a judgement of an action (or set of coordinated actions) performed intentionally/or being undertaken, designed to produce external effects, using the tools of the social sciences, according to strict and codified procedures” (Palumbo 2001: 59). If we accept this definition in the context of the evaluators’ scientific community, counting and classifying (the first two procedures) should not be fully included in the evaluation because the result of these methods is not (subjective) judgment, but simple data that could be provided by any person (including an administrator!) who has been given instructions and a spreadsheet for ranking criteria like journal quality or publisher ranking. In the third method of reading, however, the expert, whether a scientist in the discipline or research area is indispensable to judge, discern, identify, and understand the content of the publication.

Unlike the first two procedures, there is little evaluation and much monitoring. The latter, like basic research, applied research (Palumbo 2001: 64), auditing (Bezzi 2001: 65, 67), benchmarking, certifying, and social budgeting, is not evaluation. Indeed Bezzi (2001: 66) states that monitoring is the opposite of evaluating, which includes the tasks of monitoring and auditing, but is not limited to them. ← 160 | 161 → Evaluation goes further because it adds critical judgment. Counting and classifying can therefore only be a pre-condition of the evaluation, an initial screening and not an assessment itself.

3.  Against Abstractive Evaluation: Desperately Seeking Society

The two procedures (that have become dominant in the evaluation of scientific products) fall into an abstracted evaluation pattern, divorced from the social dynamics, epistemologically naive, politically inexperienced and not reflective. This pattern, ostensibly rational and transparent, does not take into account how indicators are (socially) constructed, and which representations, mental models and tacit knowledge are embedded in them.

What Makes a Person a Good Researcher: A Problem of Conceptualization

All methodological textbooks teach that in order to conduct research, it is first necessary to conceptualize the phenomenon, i.e. defining the so-called ‘object of research’. One cannot start researching family or poverty, for instance, without first defining what a family is (and we know how definitions are controversial and change over time) or what poverty is. In other words, what criteria I adopt include that particular relationship between people in the category of ‘family’, or what requirements a person must have to be defined as poor.

The same applies when it comes to evaluating a researcher. Before evaluating a researcher, you must conceptualize who (or what) is a good researcher. Before choosing performance indicators, we should discuss what the attributes (according to constructivism) or properties/characteristics (following realism) of the concept of ‘good researcher’ (the so-called ‘intention’) are. Instead, the common practice is actually moving in reverse: indicators are chosen in a confused, abstract and naïve way without reflecting on what is behind these cognitive tools or what their cultural background is. This information is then used to form the concept of what a good researcher is.

An Evaluation Without…Society

Existing tools for the assessment of scientific production measure people as if they were impersonal databases, not social entities. These tools forget that they are people with biographies and social trajectories etc. It is as if the authors and their products belong to two separate and unconnected worlds. A (welcome) opposite tendency is represented by the think tank New Economics Foundation (Nef), a ← 161 | 162 → group of 50 economists famous for bringing into the agenda of the G7 and G8 issues such as international debt, whose motto is (significantly): “Economics as if people and the planet mattered.”

Starting from the assumption (therefore theory) that there should be a direct correspondence between what we are paid and the value our work generates for society, Eilis Lawlor, Helen Kersley and Susan Steed (the authors of the Nef report) calculated the economic value of six different jobs, three paid very well and three very poorly. As the authors explain in the introduction:

We take a new approach to looking at the value of work. We go beyond how much different professions are paid to look at what they contribute to society. We use some of the principles and valuation techniques of Social Return on Investment analysis to quantify the social, environmental and economic value that these roles produce – or in some cases undermine. (4)

Following the criterion of linking salaries to the well-being that a job brings to the community, Nef concludes that bankers abandon society and cause damage to the global economy. Under this logic, when comparing a garbage collector to a tax affairs lawyer, the former contributes with his work to the health of the environment through the recycling of garbage, while the second harms society because he comes up with schemes to enable his clients to pay fewer taxes. So, when looking at the social contribution of their job, it turns out that the kinds of jobs that are paid less are actually the most useful to society.

This example shows how the assessment is primarily a social and political practice, guided by certain “theory-driven”, cultural assumptions (whether tacit or explicit) and by particular mental models of what makes (in the case of scientific careers assessment) a good researcher. It is not a simple observation based on neutral formats and criteria. As Chen and Rossi (1981, 1989), Chen (1990), Weiss (1995, 1997), Pawson and Tilley (1997) and many others have long pointed out, assessment is only secondarily a technical issue.

4.  The Tacit Assumptions of the Academic Evaluation: the Hidden Cultural Model

Given that evaluation is primarily a theoretical activity, it is worth trying to explore the main cultural assumptions (tacit and/or explicit) and the particular mental model of what makes a good researcher. In academic common sense, an ideal researcher is one who: ← 162 | 163 →

Teaches a lot and delivers high-quality teaching.

Publishes extensively, particularly scholarly or prestigious publications, but at least peer-reviewed articles and books in innovative areas of research.

Conducts good research.

Wins national and international grants.

Participates in national and international conferences.

Accepts institutional duties.

Participates in the intellectual life of the department in the form of seminars, conferences, etc.

Any academic would subscribe to the responsibilities outlined on this list (Keith and Moore 1995; Pescosolido and Aminzade 1999; Golde and Walker 2006; Sweitzer 2009).

Society Enters Evaluation: Assessment as If People Mattered

Ask ourselves now: who could perform better (equal intelligence) in all of these areas? A sociologically plausible ranking would be:

  1. Single
  2. Person with partner, without children
  3. Person with partner, with 1 child
  4. Person with partner, with 2 children
  5. Person with partner, with 3 children
  6. etc.

Intervening social factors (like having to care for a sick or disabled person, having a partner away for work, having the support of grandparents, or having access to financial resources to pay for a babysitter etc.) must be left out of consideration in this case because otherwise it becomes difficult to manage the complexity and evaluate it with standardized instruments.

Obviously, we are talking about people of both genders here, not men or women in particular. For the moment, gender does not come into play. And, when it does, it will make the evaluation even more social. If this ranking is sociologically plausible (and we will soon see how it is) other questions arise:

What is the cultural model underlying these evaluation criteria?

What tacit assumptions are embedded in it?

What is the underlying profile?

Maybe that associated with Nobel Prize winner Rita Levi Montalcini (single) or the famous astrophysicist Margherita Hack (partner, no children)? ← 163 | 164 →

Is it reasonable to assume that researchers who have had children have also experienced a drop in scientific production, defined as reduced capacity to conduct research and guarantee an institutional presence?

Female Nobel Prize Winners

An interesting example to test this hypothesis is using the Nobel Prize award, particularly because only a few women have been awarded the Nobel Prize (see Cole 1987, Wade 2002). In fact, the Nobel Prize has only been awarded to women 47 times between 1901 and 2014 (only one woman, Marie Curie, has been honored twice). During this same period, 814 men were awarded Nobel Prizes. Women’s creativity is clearly underrepresented in science.

But even more interesting for our hypothesis is the fact that many of these women did not have children (Stemwedel 2009). By comparing the 11 female Nobel laureates in physics, chemistry and physiology/medicine between 1901 and 2006 with 37 males who received the Nobel Prize in the same area one year prior and one year after them, it was found “that female Nobel laureates were significantly less likely to marry and have children. When female laureates had children, they had significantly fewer children than male laureates. Female laureates also had fewer publications than their male counterparts” (Charyton, Elliott, Rahman, Woodard and Dedios 2011: 203). These authors conclude that eminent women scientists tend to choose the pursuit of scientific discovery over starting families more frequently than prestigious male scientists.

If this were to hold true for the vast majority of women working in the academy, would it be reasonable for women to ask for a correction, a weight, an adjustment to the current assessment procedures that takes into account the number of children and the demands of care giving?

5.  The International Context and Southern Europe

Growing literature on the topic and other research shows that at least in Southern and Eastern Europe, fathers and mothers are not yet equal in their performance.

Weekly Hours

Among Europeans, Greeks work the most of all countries, with an average of 42.2 hours per week (British Office for National Statistics, 2012). The Germans, on the other hand, work only 35.6 hours. These two countries are at opposite ends of the current crisis in Europe. The hours worked and economic performance seem to be upside-down, with the hardest workers in Greece, and almost ‘lazy’ workers in ← 164 | 165 → Germany. In Bulgaria, Czech Republic, Poland, Romania, and Slovakia, people also work on average more than 40 hours per week. Denmark is even more extreme than Germany, at not even 34 hours, and Scandinavian countries in general work less than the classic 40-hour week.

One explanation for this could be the difference in productivity: Germany is dominated by well-organized companies and modern technologies, financial opportunities, supply chains and advanced distribution, and low corruption. At the other extreme is Greece, where the people work longer with less achieved. In 2012, in a measure of productivity in the European Union, Germany was at 123.7, while Greece landed at 76.3.

It must be acknowledged that it is not the number of hours worked that creates wealth and efficiency. We must understand why in many countries, workers but especially managers stay so long at the office, while women tend to concentrate their presence at work in order to take care of other domestic and family responsibilities. The reason behind this typically male behavior is that many companies’ people construct their career through relationships instead of on merit alone. Staying late in the office creates solidarity, especially among male workers because most of the women have already gone home. And in organizations where you advance through cliques, membership and loyalty are decisive factors. This is not true everywhere. But certainly at companies where workers put in long workdays are not necessarily focused on quality and productivity. Taino (2012) reports some statements of Anglophone managers: “When the clock strikes five, the team goes home,” says Max Cameron, CEO of Big Bang Technology, a hi-tech Canadian company “I tell everyone that the game is over and they lost”. Cameron believes that the mentality of the hero who sacrifices himself for the company is highly damaging to the company. On the one hand it leads to burnout, a mental disorder of those who work under stress for too long. On the other it creates an environment where no one can become a leader without sacrificing his life, who then cannot be promoted even if s/he has the qualities to be so. As Cameron says, this “erodes the leadership”.

Barry Sherman, the CEO of the American company Pep Productivity Solutions, says that the non-economic reasons why someone works overtime are twofold: “The first is that s/he does not want to go home and the second is that s/he does not know how to work effectively” (Taino 2012). People who work overtime probably do it to please their boss and advance in their career, but also because the external environment permits it. In Sweden, for example, staying at the office beyond the typical end of the workday is considered objectionable from the point of view of society; it is seen as a selfish choice and suggests that that person has no interest ← 165 | 166 → in others or the outside world, beginning with the family. This cultural belief is so dominant that only 1 percent of Swedes work more than 50 hours per week (OECD 2012) and overall men on average devote 177 minutes per day to cooking, washing and caring for children, compared to 249 minutes for women. In Italy, however, men spend 103 minutes for activities related to the family compared with 326 minutes for women. Career and social relations both inside and outside the office, therefore, explain many of the reasons for overtime.

In 2002 in Sweden, the Toyota company in Gothenburg, the second largest city in the country, switched to a six-hour working day, resulting in happier employees (in a country where winter depression affects people more than elsewhere), a lower rate of turnover and an increase in profits. This experience is also expanding in other companies in Sweden, where many employees have set themselves the goal of accomplishing more work in a shorter amount of time so they can have more time to devote to their personal lives. Filimundus, an application developer company based in Stockholm, also introduced six-hour days in 2001. “The eight working hours are not as effective as you think,” says Linus Felds, CEO of the company. “To remain fixed on the same work for eight hours is difficult. To do that, we usually intersperse work with breaks”.

Japan is a country where merit is poorly rewarded and networks of relations prevail, and where there are still high barriers between male and female workers. According to the trade unions, on average, one supervisor out of ten leaves the office after 11 pm, and 84 percent of workers generally work beyond the established working hours. To this point, Japanese has the word karoshi, which means death from being overworked. Similar situations in which workers stay at the office until the boss leaves are seen in South Korea and Singapore. Then there are those who work too much, leading to organizational dysfunction. In this case, the problem is serious for the company; it may be getting lots of overtime from its employees, but the trade-off is quality and creativity. There are also serious problems for workers: a 2012 study at the Institute for Health and Employment of Finland discovered that those who regularly work more than the classic eight hours per day had a 40–80 percent increased risk of having heart problems and ran a greater risk of developing dementia due to “prolonged exposure to stress” says Marianna Virtanen, who led the research.

Productivity and Prolongation of Working Hours: Two Variables… Inversely Proportional

A comparative analysis of dozens of companies commissioned in 2014 by the Californian company Seagate Technology reveals that managers and employees ← 166 | 167 → waste a good deal of time each day sending and replying to emails and participating in meetings. They “really” only work a few hours, and yet the time is never enough.

In one American multinational, for example, employees spend on average 20 hours per week in meetings and send or receive 3700 emails per year. A typical manager of a company this size “consumes” 400 hours a week of its employees’ time in email correspondence and meetings. “The meetings are frequently the realm of multi-tasking,” quips an expert, “people spend their time writing messages on their mobile phones, in practice not even listen[ing] to what others say” (Franceschini 2014). In addition, meetings almost always last too long: when a meeting exceeds 90 minutes, attention wanes and participants lose sense of the meeting objectives. These bad practices are especially detrimental to the careers of people who have very tight timelines at work due to their child-care commitments.

The Double Burden

In the 1970s, the first reflections on the concept of “double presence” (Balbo 1978) or “double burden” “double day”, “double duty”, “second shift” (Hochschild and Machung 1990) appeared. These expressions indicate the dual roles shouldered by women: public and private, reproductive in the family and productive in society. Under this concept, a woman is squeezed between her dual responsibilities both to the family and to her independence, represented by the work, which has a negative impact on her. This phenomenon is found in all companies and continents, naturally in different contexts and intensities. In fact, men’s contribution, in order to alleviate double burden, is understood as an option for most couples, even those who share family responsibilities equally…the male role in the allocation of family work is limited to a minimum necessary assistance (Jana 2011: 176–177).

6.  Social Policies to Reduce Gender Inequalities

Worldwide since the late 1970s, there have been numerous public policies launched in favor of gender equality. There are many different policies, some of which are potentially complementary, others ideologically incompatible due to the distinct cultural and theoretical perspectives that guide them. Let us describe these policies briefly (for more see Marra 2014). The first group of policies is focused on promoting affirmative action. First borne in the United States, they aim to overcome specific inequalities between men and women, such as instituting quotas for the boards of listed companies or universities, which aims to ensure the autonomy of women not only in terms of social distress but also (and especially) ← 167 | 168 → in the higher levels of the socio-economic and political-institutional organization of an economically advanced democracy (Shalev 2008; Marra 2014).

In contrast, in continental Europe policies in favor of women have resorted to social protection (i.e. services provided by the institutions of the welfare state, monetary transfers as maternity or illness allowances, retirement etc.) rather than the opportunities for emancipation and economic growth that the labor market could offer.

According to this second approach, it is necessary to remove “the unequal division of extra-work duties and care-giving, the inadequateness of reconciliation services (whether public or private) and the resistance by enterprises and public administrations to rethink the models of work organization” (Marra 2014).

A third group of public policies appeared in the middle of the 1990s, brought about by the European Union and international organizations. It refers to the approach known as gender mainstreaming, which originated in Northern Europe (Rubery 2002; Verloo 2005; Gornick and Meyers 2008; Knijn and Smit 2009). It argues that, since there is not a biological relationship between gender and social roles and responsibilities, the existing differences between the genders can be filled in order to make the tasks in the two main social spheres of work and family interchangeable and assimilable. This mutual replaceability would allow for the development of a more egalitarian society. According to this approach, it is necessary to remove “the unequal division of extra-work duty and care, the inadequateness of the reconciliation services (whether public or private) and the resistance of enterprises and governments to rethink the models of work organization” (Marra 2014).

Finally, a fourth group of proposals refers to more purely feminist approaches (Pillow 2002; Sielbeck-Bowen et al. 2002) that are sometimes in conflict with the gender approach, which is accused of promoting an unconscious acceptance of the capitalist model of production, tacitly embodied in the public policies they propose. Instead, feminist scholars recognize the importance of caregiving, social reproduction, and appreciate the differences women make in lifestyle choices. For them, the differences between and within genders are irreducible and an asset to society, a resource to respect and promote balancing the pressures to homologation embodied in the social organization of the most advanced economies (Marra 2014).

These four approaches are often difficult to reconcile, so much so, in fact, that it has been suggested to move beyond the feminist and gender-based approaches (Marra 2014). Let us take an illustrative example: in order to combine work with caring for young children, a society may enact different public policies including ← 168 | 169 → increasing available places in kindergartens and nursery schools; providing monetary support and contributions to help families who decide to send their children to these institutions; reducing school fees; and providing supplementary payments to cover the costs of babysitting or creating other services.

However, this logic is very functional within a model of capitalist production. What if a parent prefers not to make use of daycares or babysitters during a child’s first three years of life? In any case, what is better for a child than to spend the first years of life in close contact with (at least) one parent? Why impose institutionalization from the very first years of life for an infant? Why entrust their education to babysitters who often come from countries with highly sexist cultural models? Why abdicate our own educational tasks to grandparents or other relatives, who perhaps do not share the same educational models as those the parents wish their children to have? Due to these reasons, the balance of the burden of responsibility for family care through new welfare benefits and flexible forms of work organization cannot be tailored to suit everyone. A much better approach is the increasing number of colleges and universities that have instituted (over the last decade) a variety of policies for new parents including tenure clock extensions, reductions in teaching duties, and parental leave, to name just a few (Ward and Wolf-Wendel 2012).

However, greater equality between men and women would probably be achieved if the tasks of care were equally distributed between genders. Unfortunately, this is (still) not not a reality for most couples. Therefore, mother-scientists can hardly compete, in terms of scientific production (journalistic), with their male colleagues, whether or not they are themselves fathers. And, often, these women cannot make it.

Can We Think of Something Faster?

Several studies (Barclay and Lupton 1999; Harrington, Van Deusen and Humberd 2011; Miller 2011; Jana 2011; Hook and Wolfe 2013; Kaufman and Bernhardt 2014; Rehel 2014, Pizzorno, Benozzo, Fina, Sabato and Scopesi 2014) show that the traditional division of gender roles in child rearing is changing. A new model is emerging in which there is greater equality in managing a couple’s double careers: more and more fathers participate in family life and are involved in care-giving activities (Marotte, Reynolds and Savarese 2011). In addition, social and conciliation policies (Marra 2012), which help to rebalance care-giving activities between gender roles, are increasing. This is seen, for instance, in the increase of flexible regulation of work hours both for men and women; the increase and improvement of health services; and better reconciliation practices for women and men in ← 169 | 170 → businesses, trade unions and at the state level in civil society (see Gasauka 2011). However, these changes are slow and the effects of these policies take decades to manifest themselves.

Instead of waiting for these effects to take root, could we immediately introduce some correctives to reduce (at least partially) the existing inequality, particularly in the scientific production of the mothers, which (as we have seen) is often the first criterion used to evaluate a scientist or academic professional?

7.  For a Care-Sensitive (and Mother-Sensitive) Assessment

If care-giving results in a slowdown of scientific production, then we need an evaluation practice that takes this into account. However, because men and women currently do not participate equally in the child-rearing and family responsibilities, it becomes necessary that the assessment should be geared more towards the mothers. If men and women are different (and often unequal) in society, we cannot assume that the effects of this diversity (and inequality) are simply suspended when we turn to scientific production. The same applies to mothers. There is however currently little attention given towards providing a differentiated assessment of scientific production, which essentially assumes that men and women, fathers and mothers, are or should be equal.

Unfortunately, for Mothers … Little Data

Researchers who compare the scientific output between men and women to see if there is a real difference rarely report whether these women under study have children. There is little academic data that includes this information and has the related variable that would be useful for a more accurate assessment.

In fact, when it comes to scientific output, it does not seem reasonable to hypothesize differences between men and women if both are childless. Instead, the discussion would become more interesting if we could ascertain whether children (in addition to illness, providing care for parents, lack of livelihood etc. which here we do not consider) are a possible and important cause of the slowdown in scientific output and contribute to difficulties in doing research and participating in the institutional life of the department, conferences etc. which, again, we do not consider here. Currently there are many studies conducted in different countries which show that child rearing is still strongly attributed to the mothers.

Unfortunately, current research and comparisons rarely outsource this data and therefore do not help us to understand whether children have an impact on women’s scientific production. For example, Tower, Plummer and Ridgewell ← 170 | 171 → (2007) conducted a study on six of the top journals in the world, as rated by the 2006 Thompson ISI index. They chose two for each category: two in science (Science and Cancer Journal for Clinicians), two in business (Academy of Management Review and Quarterly Journal of Economics) and two in the social sciences (Archive of General Psychiatry and Harvard Law Review). Leaving aside the questionability of this selection (namely, I am not sure how many social scientists know of the existence of the last two journals), they found no difference in productivity when the percentage of the women participating in the academic work force is factored in: women comprised 30–35 percent of participation rates in academic university positions and represented almost 30 percent of the authors in the top-tiered journals. In addition, they did not find any significantly statistical difference in journal Impact Factor ratings between women and men. This is an example of abstractive statistical analyses, which are totally decontextualized. Because their analysis only covers six top journals, the generalizability of these results should be taken cautiously, and the authors do not check whether those women have children. They only take into consideration the (abstract) variable of gender without providing any contextual analysis to understand the biography of these women and men (e.g. age, marital status, children, etc.). The same problems are to be found in the studies by Rothausen-Vange, Marler and Wright (2005) and Dasaratha, Raghunandam, Logan and Barkman (1997).

So there only remains the option of looking at comparative research between men and women, and then weighing these results using a virtual or “thought experiment” (Gedankenexperiment) with the use of “counterfactual” conditionals (Van Dijk 1977: 79–81), a type of research used in economics, physics, cognitive sciences, history, etc. (see Gobo 2008: 151–152).

Women’s Scholarly Productivity

Much of the literature on work and family issues in academia suggests that women with children have a harder time maintaining an ideal career because of the difficulty of combining work and family activities, both of which are regarded as “greedy institutions” (Hochschild 1975). Women “are expected to (and often do) take on more child-rearing and housework responsibilities. If separated or divorced, women are more likely to be the custodial parent. There is considerable literature that women academics are hampered in their efforts to have an ideal career” (Spalter-Roth and Van Vooren 2012). According to a report from the Committee on the Status of Women in Sociology (2004): “Women may face serious disadvantages. Careers often are built … around a model of a worker who has no competing responsibilities to work and is able to devote full attention to (usually ← 171 | 172 → his) professional life. Persons who do not conform to this pattern of the unencumbered worker will be disadvantaged in achieving success within the profession”.

In a study of doctoral students at the University of California, over 70 percent reported that they considered academic careers in universities unfriendly to family life (Mason 2012). Women with children “may be unable to regularly stay late to muse over intellectual questions with colleagues at the office or a local pub, but instead may have to pick up children from school or daycare or return home to prepare dinner” (Spalter-Roth and Van Vooren 2012). In addition, women may sometimes need to bring the baby to class with them (Kennelly and Spalter-Roth 2006).

Research suggests that parenting within the academy is a gendered phenomenon. Mason and Goulden’s (2002) widely-cited study of a nationally representative sample of PhD recipients between 1973–1999 finds that raising children, especially early in one’s academic career, has a negative effect on women’s careers. However, this was not true for men. Women who have children are more likely than men with children to have marginal or alternative careers.

However, the research on women’s scientific productivity offers other controversial results, which are not always easy to interpret. Kyvik (1990) argues, on one hand, that women become more productive when the children get older, because the children are more independent and less in need of care. In the same article, amazingly enough, Kyvik also states that both men and women, married and divorced people are more productive than singles.

The latter statements are not credible in the light of the the former statements. For example, the following: women with children are more productive than women without children (Kyvik 1990). These statistics are out of context, without accounting for social dynamics. In other words, it would be important to know: who are those women with children? How many children do they have? Do they have domestic help? To which social class do they belong? Without this information, interpretation appears shaky.

According to the study by Long, Allison and McGinnis (1993), although men and women start out as assistant professors with similar levels of productivity, after six years men have significantly more publications. Kyvik and Teigen (1996) observe that in the span 1989–1991 (of their database), men had published an average of 6.9 articles, while women had only published 5.6 (20 percent less). During the same period (1989–1991), male faculty members under age 40 published twice as many article equivalents than their female counterparts, whereas for faculty over age 40 the difference is small (10–15 percent) (Kyvik and Teigen 1996). ← 172 | 173 →

From this research, some clarity begins to emerge on the differences between men and women.

Ward and Wolf-Wendel (2012) conducted a longitudinal study, interviewing over 100 women who are both professors and mothers, examining how they navigated their professional lives at different career stages. They studied how tenure-track women faculty members managed work and family in their early careers (pre-tenure), when their children were young (under the age of five), and then again in mid-career (post-tenure) when their children were older. The findings suggest that family plays a role in how people develop in their academic careers, just as careers play a role in how people evolve within their family.

Women and Bibliometric: What Happened in Italy?

In 2012, in Italy, the National Agency for the Evaluation of the University System and Research (ANVUR) settled the minimum requirements to become a full professor with a ministerial decree. Shortly after, Corsi and Zacchia (2013) did a simulation by applying the ANVUR’s bibliometric ‘recipe’ to the scientific output of female economists (full faculty members as well as potential candidates for promotion to full professor), to see how many of them satisfied the criteria established by the ANVUR. The results were surprising.

If we look at the median number of journal articles and book chapters, out of a total of 301 female economists (including 110 associate professors) only 22 percent of lecturers and associate professors satisfied the first requirement, which had a median equal to or greater than 8. Unlike for men, the percentage of success was 35 percent. If we look at the median number of books published, only 3.6 percent of female lecturers and associate professors had published at least one monograph over the past decade. In this case, the percentage achieved by males was higher than or equal to 9 percent.

Finally, if we monitor the median number of publications in top journals, the criterion of excellence of the economic disciplines SECS-P01/P06 ranges from 0 (in science of finance, economic history, history of economic thought) to 6 publications (Econometrics) in ten years. Although this was poor coverage of the top journals in the Econlit database, only 26 percent of female economists had at least one publication in the past decade included in the list of the requirements of “excellence”: specifically, 25 percent of associate professors and 27 percent of lecturers. In this case, the gender gap was more pronounced because about 90 percent of men had at least one article in the last ten years published a top journal. ← 173 | 174 →

Causes of Gender Disparities in Academic Publishing

In literature, the underproduction of academic women in research outcomes has been traced to the following root causes:

Women and men tend to collaborate with co-authors of the same sex; because there are relatively few women in faculties, women have more difficulties finding co-authors (Ashcroft, Bigger and Coates 1996; Suitor, Mecom and Feld 2001; Bentley 2003).

Females are more likely to work in non-tenure track, part-time and temporary positions, or work at teaching colleges, leaving less time for research and publishing (Dasaratha Raghunandam, Logan and Barkman 1997; Mathews and Andersen 2001; Robinson 2006), more involved in service activities at the expense of research (Dasaratha, Raghunandam, Logan and Barkman 1997; Maske, Durden and Gaynor 2003; Corley and Gaughan 2005; Robinson 2006) and disadvantaged by family responsibilities. Men spend more time at the university and less time at home, even among married faculty, especially during child-rearing years (Mathews and Andersen 2001; Bentley 2003; Suitor, Mecom and Feld 2001).

These factors are slowly changing. However, change is happening gradually, and social and cultural changes are not easily predictable. Therefore, it is necessary to do something now.

8.  Contextualizing Indicators (and Consequently Factors and Indices)

To accelerate the achievement of equality in scientific careers, it is necessary to adopt different criteria for evaluating CVs, particularly for scientific output. If, as the literature has documented, men and women indeed face different realities (and diversity management is now a reality), it is not clear why they should be treated as equal.

To this end, the proposals can be various and diverse. If a candidate is strongly committed to child-rearing, their scientific production could be evaluated in the context of how many children they have3. That the weighting can be reasonable ← 174 | 175 → is testified by the practice (now widely accepted and published) of normalizing the scientific production for the age of the candidate. So we can assume different remedies (even standardized as weights, corrective coefficients, adjustments, normalization etc.) that take into account the social dynamics and inequalities on behalf of those engaged in activities of care, in order to better assess their scientific production. For example, this could take the form of the following methods:

  1. To normalize, to attribute a score, an additive weighting etc. to those who have children.
  2. To give priority to the quality of publications, rather than quantity. Candidates could indicate three publications they consider their best, their most innovative, etc. and the assessment will be conducted on those only. So at least the referees would read them, which they do not do when they receive 20 publications.
  3. To give space on the CV to quality management (practical skills, multi-tasking, negotiation skills, ability to reconcile different commitments etc.) that come from playing a role of a mother/father strongly present in the family (see 11).
  4. To make a multidimensional assessment of research (see Tucci, Fontani and Ferrini 2010).

The Multidimensional Assessment of Research: The R Factor

In proposing a multidimensional evaluation of research, Economists Tucci, Fontani and Ferrini start from two very “social” assumptions (2010: 107):

  1. The publication of articles is only one aspect, albeit an important one, of a researcher’s scientific activity;
  2. There are a number of activities, not always visible (and not always transformed into articles and citations), which nonetheless contribute to scientific progress.

To take better account of these two assumptions, they construct what they call the “index R-factor”, which consists, in turn, of the following sub-indices:

Articles published in journals

Monographs and essays

Grey literature

Coordination activities (conferences, research groups, coordination, doctoral classes, theses supervision)

Dissemination activities (seminars, conferences etc.) ← 175 | 176 →

Type activities publishing (journal editor, board member etc.)

Administrative activities (dean, chair, coordinator, director of research centers).

Although not mentioned by the authors, additional information could also be included:

Number of teaching hours

Annual number of exams

Number of theses and dissertations supervised.

As we can see, the term “evaluation” (attributed to this proposal) is very stretched, being nothing less (and no more) than a complex monitoring. However, the proposal looks very interesting and fruitful. In addition to these indices, a “care-factor index” would also be included, built on:

Number of children

Age of children

Health status of children.

While taking into consideration other indices (such as parental capital, economic capital, etc.), even if significant, it could be complicated.

9.  The C Weighting and Its “Enemies”: Men and Women

Although there is broad consensus on the need to balance parental roles, when we move to operationalize this need through technical proposals, various opposing claims arise. The main “enemies” of the C weighting are primarily men (especially in the Latin countries, where men are generally more reluctant to split care practices with their partner) who reductively see this policy as an exclusive advantage for women. In fact, it is difficult to make it clear to men that this policy could also be applied to a father who decides to spend more time with children and family. It is no coincidence that, although in many countries there are rules allowing fathers to take advantage of parental leave (for child-rearing), requests for such leave are relatively rare: many men are ashamed to express this desire and prefer to give up the benefit rather than be exposed to jokes and macho criticism by males (and perhaps also by some female colleagues).

A second aspect concerns competition between universities: if the goal of a university is to maximize its results, it will tend to recruit candidates who publish more, do more research, have more education, are more institutionally present etc. Why should it hire or promote career advancement for those who are probably less productive? However, this type of reasoning (however widespread it may be) is based on limited rationality, unable to think globally, because ultimately the ← 176 | 177 → universities stand on (both economically and educationally) students. Moreover, the children of today could be the students of tomorrow. If for someone the reproduction of the species cannot be a positive value for the community (therefore as such not be positively evaluated), the fact remains that someone has to take responsibility for this task. Of course, we can decide to discourage reproductive activity among scientists and delegate it to the unemployed, the poor, migrants etc. However this (aberrant) plan should be explicit, and not tacitly activated in recruiting practices.

It may seem paradoxical, but there are already several generations of women in front of the C factor (as they still are or have been for years due to the affirmative action). One such example is the “wonder women”, who were famous 1940s comic characters. These mothers who spent their lives doing somersaults balancing work and family and in the face of enormous personal sacrifices “made it”, and became professors. They did not believe that having children would make them less productive. Indeed, they thought that if they made it, then other women would too, entering into a macho loop that damages younger generations of women (many of whom have raised the age of motherhood or chose not to procreate). Therefore, they believe that mothers do not need affirmative actions to win the men’s competition.

10.  Conclusions

Several research studies on care-giving highlight how it has had an impact on a scientist or academic’s productivity, causing a related slowdown. The latter could prove to be detrimental when the candidate takes part in recruiting or promotion processes, as the number of publications is often used as an important criterion in evaluation.

Reconciliation policies are certainly a useful tool to help dilute this effect. It is also important to promote family-friendly cultures, environments and workplaces. Institutions of higher education are increasingly recognizing that being family friendly is an asset in terms of recruiting and retaining top faculty members (Evans and Grant 2008; Ward and Wolf-Wendel 2012; Mason, Wolfinger and Goulden 2013). However, they require social and cultural changes that are (unfortunately) not immediate. So practical proposals in the short and medium term to reduce inequalities in scientific careers are urgently needed. Affirmative action examples include company laws in which one third of the members of boards of directors of listed companies and publicly owned corporations must be women. There are also short and medium-term affirmative action policies (e.g. valid for 10 years) within which it is hoped to achieve the goal of removing the obstacles that have so far ← 177 | 178 → limited women’s access to leadership roles, encouraging a process of cultural renewal in support for greater meritocracy and growth opportunities. Through these actions thousands of women had (and continue to have) the opportunity to take on leadership roles. That said, it would not hurt to extend this rule to academic staff such as the university senate and the boards of directors of the university.

One of these affirmative action policies in the academy could be the use of the Care Factor, a tool to weigh the scientific productivity of a candidate who is involved in child-rearing. It is a transitional instrument, certainly not permanent, but useful to balance the gap between those who are involved in care activities and those who are not.

However, the Care Factor should not be conceived of as a proposal that rewards those who care for children. It is not meant to reward those with care-giving responsibilities, but these people should also not be penalized. The care activity should be enhanced even further and become one of the different criteria for recruitment and promotion. In fact, child-rearing is not to be conceived exclusively as a burden, a responsibility outside the realm of academic activities. Unfortunately, as Ward and Wolf-Wendel (2012) show, much of the existing literature on balancing work and family presents a pessimistic view and offers cautionary tales of what to avoid and how to avoid it. In contrast, child-rearing brings sorely needed skills into the academy, like every other working sphere. As Balbo (1978) theorizes, the “double presence” is a way to “pass through many worlds” and thus be more innovative in both work and family. Competences and practical skills learned from juggling tasks in many areas, from negotiating and reconciling different needs to mediating between different instances, come in handy especially in collective dimensions of research work, as well as in the management of the university.

The viability of the Care Factor is being shown by Acumen, an EU Seventh Framework Program funded European project, which aims to find assessment parameters, not so much of the research as the work of researchers. For example, in its Guidelines for Good Evaluation Practices (April 2014), the calculation of academic age is based on a conventional value, which considers the number of children raised (p. 10), special allowances and other ‘penalizing’ factors (like illnesses, part-time jobs etc.).

The dream is that examples like Carol V. Robinson become much more common: Robinson went to work at age 16, then graduated and earned a bachelor’s and a master’s degree and finally, a PhD in chemistry. She then left the university for eight years to raise three children. Upon her return, she gained a professorship at Oxford on the basis of her research, becoming the first full female professor in ← 178 | 179 → chemistry. She also earned countless awards, including Dame Commander of the Order of the British Empire.

Robinson succeeded without the Care Factor. However, hers is also an isolated case. Can we do something to make her experience more widespread? The Care Factor helps us move forward in this direction.

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1 I wish to thank Emanuela Abbatecola, Maria Carmela Agodi, Miriam Bait, Marina Marzia Brambilla, Diana Urania Galetta, Chiara Guglielmetti, Mita Marra, Antonella Nappi, Gloria Regonini, Paola Ronfani, Renata Semenza, Silvia Salini and Anna Lisa Tota for comments and suggestions.

2 This is precisely the criticism contained in the Declaration on Research Assessment (DORA), drawn up by a group of editors and publishers of scientific journals, gathered in San Francisco, California, on December 16, 2012 at the annual meeting of the American Society for Cell Biology (ASCB). Since then, this declaration has been signed by hundreds of organizations (scientific journals and associations) and thousands of scholars. Joining DORA commits to supporting the adoption of scientifically correct research practices evaluation. DORA contains 18 recommendations addressed to the different actors of the research world: funding agencies, institutions, publishers, organizations producing bibliometric data and individual researchers. One of them insists on eliminating the use of metrics related to journals – like Impact Factor – for funding, recruitment and promotions (or) as a surrogate measure of the quality, or to evaluate the contribution of the individual scientist, or decisions relating to recruitment, promotion and funding.

3 Obviously taking into consideration that the number of children owns cardinal properties only apparently: in fact three children are not 3 times 1 son. Again social dynamics should be taken into account, because the burden of caring for three children depends on many factors: whether there are twins, how many years apart the children are from each other, etc. This is why when society also enters into the equation, mathematics will be (welcome, but) always too late.