The Precision Health and Everyday Democracy (PHED) Project: Protocol for a Transdisciplinary Collaboration on Health Equity and the Role of Health in Society
Bibliographic record
Abstract
BACKGROUND: The project "Precision Health and Everyday Democracy" (PHED) is a transdisciplinary partnership that combines a diverse range of perspectives necessary for understanding the increasingly complex societal role played by modern health care and medical research. The term "precision health" is being increasingly used to express the need for greater awareness of environmental and genomic characteristics that may lead to divergent health outcomes between different groups within a population. Enhancing awareness of diversity has parallels with calls for "health democracy" and greater patient-public participation within health care and medical research. Approaching health care in this way goes beyond a narrow focus on the societal determinants of health, since it requires considering health as a deliberative space, which occurs often at the banal or everyday level. As an initial empirical focus, PHED is directed toward the health needs of marginalized migrants (including refugees and asylum seekers, as well as migrants with temporary residency, often involving a legally or economically precarious situation) as vulnerable groups that are often overlooked by health care. Developing new transdisciplinary knowledge on these groups provides the potential to enhance their wellbeing and benefit the wider society through challenging the exclusions of these groups that create pockets of extreme ill-health, which, as we see with COVID-19, should be better understood as "acts of self-harm" for the wider negative impact on humanity. OBJECTIVE: We aim to establish and identify precision health strategies, as well as promote equal access to quality health care, drawing upon knowledge gained from studying the health care of marginalized migrants. METHODS: The project is based in Sweden at Malmö and Lund Universities. At the outset, the network activities do not require ethical approval where they will not involve data collection, since the purpose of PHED is to strengthen international research contacts, establish new research within precision strategies, and construct educational research activities for junior colleagues within academia. However, whenever new research is funded and started, ethical approval for that specific data collection will be sought. RESULTS: The PHED project has been funded from January 1, 2019. Results of the transdisciplinary collaboration will be disseminated via a series of international conferences, workshops, and web-based materials. To ensure the network project advances toward applied research, a major goal of dissemination is to produce tools for applied research, including information to enhance health accessibility for vulnerable communities, such as marginalized migrant populations in Sweden. CONCLUSIONS: There is a need to identify tools to enable the prevention and treatment of a wide spectrum of health-related outcomes and their link to social as well as environmental issues. There is also a need to identify and investigate barriers to precision health based on democratic principles. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/17324.
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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 | 0.162 | 0.143 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.005 | 0.010 |
| Research integrity | 0.009 | 0.013 |
| Insufficient payload (model declined to judge) | 0.116 | 0.029 |
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".