Strengthening health system resilience : what role for migrants and migration policies?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Catastrophic events occurring over the last decade or so have highlighted the need to understand how to govern health systems in the face of shocks. In high-income countries this was triggered by the economic crisis from 2008 and in low and middle-income countries by the sudden outbreaks of infectious diseases, like Ebola, as well as civil conflicts, with catastrophic consequences (Barasa, Mbau et al. 2018). Most recently, the emergence and rapid spread of COVID-19 has severely tested almost all health systems around the world (Bozorgmehr, Saint et al. 2020). National responses have varied greatly, with some countries being more successful than others in containing the transmission and preventing deaths. Nevertheless, health systems in many countries have found themselves struggling to cope with the exponentially accelerating number of cases through different waves, while health systems in other countries have also come under enormous pressure (Sagan, Thomas et al. 2020).
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it