Bibliographic record
Abstract
Purpose The purpose of this paper is to present a comparative case study of national innovation system in Canada and Sweden from the perspective of gender equality. The case study focuses on public policy to illuminate the formal aspects of innovation systems as they are conceived by the state in relation to gender, diversity and social inclusion. Formal policy measures are contrasted with interview data to provide a holistic picture of innovation policy as it relates to gender equality in both countries. Design/methodology/approach This paper relies on data from 44 qualitative interviews with innovation leaders in the public sector, private sector and academia in Canada and Sweden, as well as a sample of innovation and gender experts at the Organization for Economic Cooperation and Development (OECD), in Paris, France, between 2012 and 2014. The theoretical framework draws on feminist institutionalism to explain the gendered interactions of institutions in innovation spaces. Findings This study finds that Sweden is a global policy leader in the development of gender-conscious innovation policy, while Canada has yet to consider a gender-conscious approach to innovation policy. Gender-conscious innovation policy norms have not traveled across the OECD because of administrative solos and political opportunity structures. Research/limitations implications Each of the people contacted to sit for an interview was chosen primarily on their professional title and their ability to speak from a place of knowledge about innovation in their country and or industry, and this creates a success bias within the study focusing on the knowledge of elites in the field. Practical implications This study explores how policy might be reimagined to support gender equality and diversity, thus changing the institutional landscape to support a wider range of innovations and distributing the benefits of innovation in a more equitable way. Social implications This paper challenges assumptions about the social and economic power dynamics reflected in current innovation systems in Canada and Sweden. Originality/value This is the first study of its kind in comparative public policy to explore differences in gender equality and innovation policy in Canada and Sweden. This research also contributes more widely to the existing body of gender, public policy and innovation literatures in Canada and Sweden, respectively.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.040 | 0.016 |
| Scholarly communication | 0.015 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".