On the Interrelationship Between Global and Public Health and a Healthy Environment: A Discussion with Professor Linda Selvey
Bibliographic record
Abstract
ABSTRACTDr. Linda Selvey is currently associate professor in the School of Public Health at Curtin University in Perth, Australia. She is not only a renowned Public Health physician but also has a PhD in Immunology. Her remarkable career includes projects and campaigns around the globe, encompassing countries such as Australia, Nepal, India, the Philippines and Liberia [1,2]. More recently, she was involved in the response to the Ebola epidemic and worked for the World Health Organization as a Field Coordinator for the Montserrado County in Liberia [3].In the early 1980s she became an active environmentalist and is particularly passionate about climate change and its health implications. She has been involved in many environmental campaigns and between 2009 and 2011 she was CEO of Greenpeace Australia Pacific. Based on her huge experience in both global (and public) health and medicine, she often emphasizes on the strong links between environmentalism and health advocacy. These are going to be discussed in the interview below, including useful advice for medical students interested in global and public health.RÉSUMÉDre Linda Selvey travaille actuellement comme professeure agrégée au sein de l’École de santé publique de l’Université Curtin à Perth, en Australie. Détentrice d’un doctorat en immunologie, son travail en santé publique se distingue par de nombreux projets internationaux l’ayant menée dans divers pays, y compris l’Australie, le Népal, l’Inde et les Philippines. Elle a également récemment participé aux efforts de contrôle et d’éradication de l’Ebola au Liberia en tant que coordinatrice sur le terrain pour l’Organisation mondiale de la Santé [1-3].Depuis les années 1980, Dre Selvey a une passion pour le changement climatique et ses effets parfois délétères sur l’homme et la santé publique. Cet intérêt s’est traduit entre autres par plusieurs campagnes pour l’environnement, allant jusqu’à siéger comme PDG de Greenpeace pour la région Australie Pacifique. S’établissant sur de longues années d’expérience, Dre Selvey préconise aujourd’hui une surveillance étroite entre la santé publique et l’environnement. C’est avec cela en tête que nous nous sommes entretenues avec Dre Selvey. Cet entretien comprend entre autres des recommandations pour les étudiants en médecine qui s’intéressent à la santé publique.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.037 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.022 |
| Scholarly communication | 0.012 | 0.018 |
| Open science | 0.005 | 0.017 |
| Research integrity | 0.026 | 0.061 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".