Canadian Nanotechnology and Equity Challenges: Implications for Pro-Poor and Gender-Inclusive Policy
Bibliographic record
Abstract
Nanotechnology has been hailed as a disruptive technology that would revolutionize existing products and processes, open up new markets and business opportunities, as well as offer socio-economic benefits. Research and development (R&D) in this emerging technology presents great importance to many nations, offering a significant technological advantage that gears towards economic growth. However, despite the immense promise of societal benefits from nanotechnology applications, nanotechnology might expose societies to various forms of inequities. The main objective of this thesis is to examine two priority dimensions of equity concerns related to nanotechnology: the lack of R&D for nanotechnology applications that (predominantly) benefit developing nations (pro-poor R&D) and the scant representation of women in nanotechnology fields. This study adopts a combined use of bibliometrics, social network analysis, and survey results to perform both dimensional and cross-dimensional analysis, providing a better understanding of both issues and of how the two are related. The focus of this study is on Canada, a country who prioritizes nanotechnology research and development in its science and technology strategy, and actively practices gender fairness in the scientific system and is strongly involved in international development through its R&D efforts. \nThe findings reveal that only a narrow spectrum of Canadian nanotechnology articles and patents reflect pro-poor priorities, and acknowledge the importance of promoting and leading research and innovation in pro-poor areas, as it holds the potential to promote the economic development both within and between nations. However, these pro-poor scientific and innovative efforts tend to be highly male-dominated in terms of the scientific community and the workforce involved. Gender differences in citation and journal impact of papers published in the nano-pro-poor applications reveal the presence of the Matilda effect at the level of first-authorship and a strong selection effect at the level of last-authorship for women. While the majority of male authors and male inventors collaborate exclusively with men, those involved in a mixed-gender team outperform male-only teams. Therefore, it is important that policymakers pay attention to both gender and pro-poor initiatives simultaneously, because practices to promote pro-poor innovation might result in a wider gender gap and adversely affect social development. Furthermore, gender analysis of nanotechnology scientific reward system confirms that the gender productivity gap remains a challenge in the field and that these gaps are reinforced by the fact that the most productive researchers are less likely to collaborate with women. The results also show the amount of extra effort that women must devote to their research to retain their top status in academia, and the extent that their recognition when in top positions is fragile compared to men. This study also confirms the cumulative advantage of creating a gender-inclusive culture that enables women to improve their scientific productivity and impact. The results of this study have strong implications for policy development (or reform) targeting both gender equality and poverty alleviation in emerging interdisciplinary areas, promoting a more equitable and inclusive society.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".