Unpacking gendered dynamics in livestock vaccination: Toward more inclusive health strategies
Bibliographic record
Abstract
Abstract Livestock are vital to the health and economic stability of communities worldwide. However, infectious diseases threaten both animal and human health due to losses in livestock, decreased production, and transmission of zoonotic diseases. To manage and mitigate these risks, access to livestock vaccines is critical. This is often gendered, with societal and cultural norms influencing barriers to access. Through a scoping review of 49 publications, we describe the gendered dynamics of livestock vaccination in relation to farmers’ perceptions and knowledge about vaccines, access to vaccines and vaccination programs, and the ways in which roles and responsibilities in relation to cultural norms shape and limit women’s decision making power and empowerment to participate in such initiatives. We find that across communities, women face similar barriers to engaging in livestock vaccination programs, but that local context is critical to understanding and addressing these barriers. Within a broader context of the gendered dynamics of vaccination for both human and animal health, we highlight the need for vaccination programs that identify and address inequitable access to vaccines to support community and animal wellbeing as well as resilience to emerging health threats. One Health impact statement This article examines the gendered dynamics of livestock vaccination, emphasizing the need for a One Health approach to develop more equitable and effective vaccination strategies. By considering the intersection of human, animal, and environmental health, this review highlights structural inequities in vaccine distribution and access, the impact of gender roles on decision making and participation in vaccination programs, and the broader implications for animal health and community wellbeing. Drawing on insights from veterinary medicine, social sciences, and public health, we advocate for inclusive, gender-transformative programs that address the diverse needs of those involved in livestock care and community health.
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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 | 0.025 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".