Bibliographic record
Abstract
Background: The recognition of the importance of social conditions informed early public health responses to infectious disease epidemics.By influencing exposure, vulnerability, and access to health services, social determinants of health (SDOH) continue to cause inequalities in infectious disease distribution.Such preventable and unjust inequalities are considered to be inequities.Analysis: A number of challenges and barriers exist to more widespread public health action that addresses SDOH and inequities, including a lack of clarity on what public health should or could do.The National Collaborating Centre for Determinants of Health (NCCDH) has identified four primary roles for public health action on SDOH and inequities.This paper describes these roles and includes examples of their application to infectious diseases.The critical contribution that organizations make in providing the leadership and support for programs and staff to pursue action on SDOH and inequities is also highlighted.Conclusion: While the challenge is large and complex, approaches such as the NCCDH roles for public health action provide a menu of options to facilitate the analysis and action to address SDOH and inequities in infectious diseases.
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 | 0.033 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.007 | 0.018 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.013 | 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".