Critiquing Canada's Research Culture: Social, Cultural, and Political Restraints on Women's University Careers.
Bibliographic record
Abstract
Introduction The United Nations reports that are starkly underrepresented among researchers worldwide (The World's Women 2010, 68): women are half the world's population, majority of tertiary level students in most countries, hold 44% of PhD's, but constitute only slightly more than quarter [29%] of all researchers. (1) Researchers are defined as professionals engaged in the conception or creation of new knowledge, products, processes, methods and systems, as well as in the management of these projects. (2) At the top research rank--full professor or grade A researcher--statistics vary from around 10% to over 30% within Europe alone, but a profound gender imbalance is still observed in vast majority of countries (She Figures 2012, unpaged). This pattern of gender imbalance exists also in national parliaments: the world average for women's representation is 20% (Women in National Parliaments, July 2012). Statistics for Canada are similar to international averages. Women are half the population, and, for generation, have been half or more of graduating university students, with the percentage of PhD's earned by women rising from 24.2% in 1981 to 44.2% in 2008 (CAUT Almanac 2011-12, Table 3.20, p. 39). Yet men still hold over three-quarters of full professorships and top research positions in universities and affiliated teaching hospitals. The latest data (for 2010) show that women only 23.4% of Canada's full professors. Furthermore, men are three-quarters of Canada's Members of Parliament, who set the budget for the country's major research councils--the Canadian Institutes of Health Research (CIHR), Natural Sciences and Engineering Research Council (NSERC), and Social Sciences and Humanities Research Council (SSHRC). Two recent, billion-dollar, federal government research programs in Canada, focused mainly on science, technology, and engineering, have highlighted and exacerbated gender inequities. Of 2,000 millennium Canada Research Chairs (CRC's), 25.1% overall have been awarded to women, with the figure for the higher Tier 1 level CRC's falling to 17.1%. The new Canada Excellence Research Chairs (CERC's), which offer some of the most generous research conditions in the world, have an even worse record: the inaugural appointments, made in 2010, went to 19 men, 0 women--in hockey language, shut out. Responding to national outcry, the government turned to the Council of Canadian Academies, an arm's-length federal think tank, which assembled an Expert Panel on Women in University Research. This group (of which I am member) prepared report entitled Strengthening Canada's Research Capacity: The Gender Dimension (to be released online in October 2012). With the old myths of women's natural inferiority having been dealt death-blow in the Larry Summers debacle at Harvard University in 2005 and laid to rest in the massive report entitled Beyond Bias and Barriers, the Canadian panel was generally free to set aside biology-is-destiny debates about women's and men's brains to focus on the dozens of social, cultural, and political factors that are still operative over the life-course of individuals and in postsecondary institutions and their affiliated teaching hospitals, where most of Canada's research takes place. A comprehensive literature review points to multiple, interconnected restraints, which may be grouped into four main categories. 1. upstream (home and school) factors, such as family support and teachers' encouragement during childhood and teen years when education and career aspirations are forming, influenced by such things as class, racialization, and gender, often leaving girls with less confidence in their abilities, especially in math, even when their achievement scores are the same as boys'; 2. social (community) factors, such as gender stereotypes or schemas, unequal access to social capital, unfair divisions of labour at home and at work, wage gaps, lack of childcare, and uncoordinated K-12 school hours and work hours; 3. …
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.033 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.014 |
| Science and technology studies | 0.080 | 0.046 |
| Scholarly communication | 0.033 | 0.009 |
| Open science | 0.006 | 0.013 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".