The Stockholm Paradigm: Lessons for the Emerging Infectious Disease Crisis
Bibliographic record
Abstract
The emerging infectious disease (EID) crisis represents an immediate existential threat to modern humanity. Current policies aimed at coping with the EID crisis are ineffective and unsustainably expensive. They have failed because they are based on a scientific paradigm that produced the parasite paradox. The Stockholm paradigm (SP) resolves the paradox by integrating four elements of evolutionary biology: ecological fitting, sloppy fitness space, coevolution, and responses to environmental perturbations. It explains why and how the EID crisis occurs and is expanding and what happens after an EID emerges that sets the stage for future EIDs. The SP provides a number of critical insights for changing scientific and public policy in a manner that allows us to begin coping with the EID crisis in an effective manner. It provides hope that we can anticipate EIDs and prevent them or at least mitigate their impacts. This article has been produced in support of and with appreciation for the efforts by Gábor Földvári of the Institute of Evolution, Centre for Ecological Research, and the Centre for Eco-Epidemiology, National Laboratory for Health Security (both located at 1121 Budapest, Konkoly-Thege Miklós út 29-33, Hungary). Through his untiring efforts, team building, and leadership, he has secured the first EU-wide team research grant. This work was supported by the National Research, Development and Innovation Office in Hungary (RRF-2.3.1-21-2022-00006) and the COST Action CA21170 “Prevention, anticipation and mitigation of tick-borne disease risk applying the DAMA protocol (PRAGMATICK),” which represent the first funded efforts to apply the principles of the DAMA protocol.
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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 | 0.015 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.019 |
| Scholarly communication | 0.011 | 0.020 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.009 | 0.013 |
| 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".