A cross-dimensional analysis of nanotechnology and equality: examining gender fairness and pro-poor potential in Canada’s R&D landscape
Bibliographic record
Abstract
This study provides a cross-dimensional analysis of two equity concerns related to Canadian nanotechnology, investigating the relationship between the development of nanotechnology applications that benefit the poor and the gender gap in the scientific workforce. Many affluent countries, like Canada, aspire to use R&D to reduce inequality in both economic and gender dimensions, which makes cross-dimensional analyses essential for responsible innovation to fully understand how technologies affect equality and to guide policy. Relevant publications and patents are analyzed to explore if Canadian nanotechnology was addressing the needs of the poor and then to examine gender disparities in research and innovative advancements of pro-poor applications of nanotechnology. Only a small percentage of analyzed articles and patents reflected pro-poor priorities and Canadian workplaces involved in pro-poor nano-applications were largely male-dominated. Results suggest that coordination between pro-poor and gender-responsive policies is needed to promote both more equitable and more inclusive forms of innovation.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.011 | 0.015 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| 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".