Structural barriers to knowledge transfer and exchange among men and women in low-, middle- and high-income countries: an international cross-sectional study with vaccine researchers in 44 countries
Bibliographic record
Abstract
Abstract Background Globally, women constitute 30% of researchers. Despite an increasing proportion of women in research, they are still less likely to have international collaborations. Literature on barriers to knowledge transfer and exchange (KTE) between men and women remains limited. This study aimed to assess perceived gender barriers to KTE activities in vaccination-related research in low-, middle- and high-income countries. Methods This was a cross-sectional data assessment from a self-administered questionnaire distributed to researchers in the field of vaccination research. The administered questionnaire was developed and validated by WHO and McMaster University. Descriptive statistics were carried out. Structural factors of KTE were assessed using 12 statements measured with a five-point Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree). An index ranging from 12 to 60 points was created to assess structural factors of KTE, with higher score indicating fewer perceived barriers. Multivariable linear regression modelling was applied to examine the association between KTE barriers and gender. Results A total of 158 researchers were included in the analysis. Regardless of gender and country of affiliation, researchers experienced challenges with respect to KTE activities; particularly factors related to the availability of human and financial resources and level of technical expertise among their target audience. We were also able to identify perceived facilitators among men and women, such as the presence of structures that link researchers and target audiences, the investment of target audiences in KTE efforts and the presence of stable contacts among target audiences. Our linear regression analysis showed that women perceived more barriers than men (R2 = 0.014; B = −1.069; 95% CI −4.035; 1.897). Conclusions Men and women shared common perspectives on barriers to KTE. KTE activities could be strengthened by improving structural efforts to reduce gender differences and increase collaborations between researchers and their target audience.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".