Lecture notes

Week 4The Social Construction of Science

Do citations tell us about influence

• Of the 55 Nobel laureates working in the United States in 1963, a full 34 had studied or collaborated with a total of 46 previous prize-winners (Zuckerman 1977). Those who had worked with laureates before doing their own important research received their prizes at an average age of 44, against 53 for the others. Clearly scientists tend to form elite groupings. (p. 36)
• Francis Bacon thought the inductive benefit of science would level the differences amongst intellectual abilities.
• But a small number of authors publish many papers. 10 per cent of scientific authors produce 50 per cent of all scientific papers (as of 1986). 80 per cent of citations are to 20 per cent of papers.

Cole and Cole: scientific funding

• Funding is often placed in the hands of the most influential.
• Or institutions that have a history of success and have built public trust, largely as a result of simply being around for a long time.
• Funding opportunities contribute to stratification.
• Citations are not the only measure of success.

Contributions of productivity

• There is not one clear or obvious measure of productivity.
• One survey builds a picture of the most productive scientist as someone who is driven, has a strong ego, has a history of acting autonomously, plays with ideas, tolerates ambiguity, is at home with abstractions, is detached from non-scientific social relations, reserves mornings for writing, works on routinised problems, is relatively young, went to a prestigious graduate school, had a prestigious mentor, is currently at a prestigious place of employment, has considerable freedom to choose their own problems, has a history of success, and has had previous work cited. (Fox 1983)
• A recent study gives more abstract behavioural categories, in order of importance: persistent, smart, civil, creative, entrepreneurial, aggressive, tasteful, confident, adaptable. (Hermanowicz 2006)
• Scientists are more productive and published more in their mid-forties, and this then decreases. The reason productivity decreases with age is unclear.
• Institutional prestige is a predictor of productivity. Those hired at these institutions are highly competitive and the distinctions between candidates are very slight.
• So how does prestige contribute to productivity? Facilities and networking are typically better. Prestigious environments might provide more intellectual stimulation, or be ones where internal pressure and rewards for productivity are greatest. Or they provide more motivation by providing more visibility, and therefore more rewards for researchers. If this is right then prestige by itself makes people's research valuable.
• Cumulative advantage hypothesis: success breeds success. This helps see scientific success as elitist and idiosyncratic where it looks merit based.

Discrimination

• In the United States in 2005, women earned 46 per cent of doctoral degrees in the social sciences, natural sciences and engineering, up from 31 per cent a decade earlier. Women earned 49 per cent in the biological sciences and only 18 per cent in engineering.
• In the United States in 2006, only 19 per cent of senior faculty in these areas were women, heavily concentrated in the life and social sciences. Her aside: the social sciences and humanities are doing better, but not philosophy.

Margaret Rossiter's historical study of women in America

• Feminisation is linked to a lowering of status, and masculinisation to an increase of status.
• 1982: men perceive their work to be less masculine because of female presence. Women were then forced into the invisible sciences, the less prestigious ones such as home economics and nutritional science.
• Feminisation of fields: sociology, economics, biology, chemistry. These became more poorly regarded because they were not hard sciences or not masculine sciences.
• The golden age of science in the United States after the Second World War was a dark age for women, because more men were hired into the institutions where women had been working during the war.
• The 1960s saw the rise of many anti-discrimination laws, as a result of the discrimination of the 1940s and 1950s.

Pipeline: women in science and engineering

a pipe with leaks at every joint along its span, a pipe that begins with a high-pressure surge of young women at the source, a roiling Amazon of smart graduate students, and ends at the spigot with a trickle of women prominent enough to be deans or department heads at major universities or to win such honours as membership in the National Academy of Science or even, heaven forfend, the Nobel Prizequoted on her slide

• Science is losing women along the way. The intake into the pipeline also matters: women need to get in and stay in.
• Getting in, staying in, getting on.

The stereotypes continue

• An analysis of advertisements in the journal Science shows that there is more cultural content between the covers of Science than we would care to acknowledge (Barbercheck 2001). Men are more likely to be depicted as scientific heroes, as nerds or nonconformists, and at play. Words like simple and easy are more likely to go with pictures of women; fast, reliable and accurate with pictures of men. Female figures can serve as symbols of nature in a way male figures cannot.

We would all go to parties together and go and have beer on Friday, but if somebody came in to ask what drying agent to use to clean up THF, they would never ask me. It just wasn't something that would cross their mindsa female doctoral student, Etzkowitz et al. 2000: 74

• Peer review scores for postdoctoral fellowships at the Swedish Medical Research Council: reviewers rated men's accomplishments as overwhelmingly more valuable than apparently equivalent accomplishments by women (Wenneras and Wold 2001).

For a female scientist to be awarded the same competence score as a male colleague, she needed to exceed his scientific productivity by approximately three extra papers in Nature or Science, or 20 extra papers in an excellent specialist journal such as Atherosclerosis, Gut, Infection and Immunity, Neuroscience or RadiologyWenneras and Wold 2001

• Young female scientists are often discriminated against by: being given smaller labs than their male counterparts; accepting or negotiating worse startup conditions, such as lower grants or salary and increased teaching duties in place of research requirements; being excluded from informal networks, and therefore not being part of the community of scientists.
• In individual cases such differences can appear trivial, but if competition is strong enough they may have a substantial effect. If the cumulative advantages and disadvantages are strong enough, the small irritants women face, and may even shrug off, can be enough to keep them from getting on. (Cole and Singer 1991)

Do women learn differently?

• Genetics. There have been claims of a math gene or similar biological propensity accounting for boys' better abilities in mathematics and science (Benbow and Stanley 1980), and as recently as 2005 Harvard's president Lawrence Summers invoked biology to explain differences in men's and women's success in science and engineering. Given that genes only act in environments, such claims are ideological statements, and they also run against recent trends in which boys' and girls' mathematics test scores are becoming closer. (Etzkowitz et al. 2000)
• Distinctive learning patterns. A number of feminists and non-feminists have claimed that women and men tend to have distinctive patterns of learning and thinking (Gilligan 1982; Keller 1985). Women, it is argued, tend to think in more concrete terms than men, and are thereby better served by problem-centred learning.

Conclusion: accumulative process of exclusion

• There is no one reason that keeps women out of science.
• Science looks much more like a boys' club than a meritocracy.
• Those in elite positions produce more, due to a combination of competitive advantages.
• Her last line is a pointer with nothing under it: British Association for the Advancement of Science example. That one was given in the room.

Wednesday 30 SeptemberThe social construction of scientific and technical realities

Social construction

• The construction of facts, knowledge, theories, phenomena, science, technologies, societies.
• Truth, rationality and the material world have limited value without interpretation or rhetorical work.
• Science and technology are importantly social.

The realist position, and Hacking

• Ian Hacking, 1999, wrote on constructivism. Constructivism against realism on scientific theory.
• Realism is the intuition that truths are mostly dependent on the natural world, and not on the people who articulate them. There is a way that the world is, and it is possible to discover this way and represent it accurately.

Social constructivism

• Originates from Max Weber, Karl Marx and Émile Durkheim.
• Sociology of knowledge: science is not just science, and scientists construct facts.

Insofar as all human knowledge is developed, transmitted and maintained in social situations, the sociology of knowledge must seek to understand the processes by which this is done in such a way that a taken-for-granted reality congeals for the man in the street. In other words, we contend that the sociology of knowledge is concerned with the analysis of the social construction of reality.Berger and Luckmann 1966: 3

To construct an X in the social world we need only that: (a) knowledge of X encourages behaviors that increase or reduce other people's tendency to act as though X does or does not exist; (b) there is reasonably common knowledge of X; and (c) there is transmission of knowledge of X. Given these conditions, X cannot be wished away, and so it exists. For example, gender is real, because it is difficult not to take account of it. Gender structures create constraints and resources with which people have to reckon. As a result, treating people as gendered tends to create gendered people. Genders have causal powers, which is probably the best sign of reality that we have. At the same time, they are undoubtedly not simply given by nature, as historical research and divergences between contemporary cultures show us.Sismondo, quoted on her slide

• What this covers in science: knowledge, methods, epistemologies, disciplinary boundaries, style of work.
• The social reality of knowledge is a precondition for progress.
• Claims do not just spring from the subject matter into acceptance, via passive scientists, reviewers and editors. It takes work for them to become important.

Example: laboratories

• Karin Knorr Cetina: nature is not to be found in the laboratory (1981). To the observer from the outside world, the laboratory displays itself as a site of action from which nature is as much as possible excluded rather than included (1983).
• Spaces of prepared materials for use. The place is intentionally shaped and manipulated. These are not real worlds.

Technology and science shape the material world

• Her example: cars made suburban cityscapes possible.
• Her second example, gender differences. Research into the causes of gender differences has the effect of naturalising those differences. There is tremendous public interest in the area, so biological research on genes linked to gender, on the gender effects of hormones, and on brain differentiation between men and women tends to be well reported. More often than not it is reported to emphasise the inevitability of stereotypical gendered behaviour, and there is good reason to expect that this reporting has effects on gender itself.
• Science shapes policy: government actions are increasingly held accountable to scientific evidence.

Construction of theories

• Methods of transforming data into representations. The most straightforward use of the metaphor in STS describes scientists and engineers constructing accounts, models and theories on a basis of data. Science is constructive in a geometrical sense, making patterns appear given the fixed points that practice produces.
• Representations of nature are connected to nature, and are not implied by the data. Scientific and technological theories are constructed with reference to data, and the data does not imply them.

Heterogeneous construction

• The various constructions can be parcelled out for analysis, and in practice they are bound together. Builders of technology do heterogeneous engineering (Law 1987): they have to build artefacts and build the environments in which those artefacts can function at the same time, and typically neither can be done on its own.
• Technologists need to combine raw materials, skills, knowledge and capital, and to do this they must enrol any number of actors, not all of whom may be immediately compatible. These networks combine isolated parts of the material and social worlds: laboratory equipment, established knowledge, patrons, money, institutions. No one piece of a network can determine the shape of the whole.
• Science and social order are co-produced. Good climate science is based around good policies.

Construction of kinds

• Nominalists: kinds are human impositions, even if we share classifications easily. Objects are a mental and linguistic phenomenon.
• Realists: kinds are real features in the world.

Conclusion

• Science gains power from, among other things, its ability to manipulate nature and measure nature's reactions, and its ability to translate those measurements across time and space to other laboratories and other contexts.
• Laboratories and technology contribute to objectivity and objective knowledge.