Institutional origins of COVID-19 public health protective policy response (PPI) data set v. 1.2 - regional U.S. and Canada
Bibliographic record
Abstract
This is an original dataset of stringency of public health policy measures that were adopted in response to COVID-19 worldwide by governments at different levels January 24 and April 30 2020. The national file includes daily national level aggregates for 64 countries. The regional file includes daily sub-national level aggregates for Canada and the USA. To measure COVID-19 mitigation policy responses, we gathered data on policies that national and subnational policymakers adopted within fifteen public health categories: state of emergency, self-isolation and quarantine, border closures, limits on social gatherings, school closings, closure of entertainment venues, closure of restaurants, closure of non-essential businesses, closure of government offices, work from home requirements, lockdowns and curfews, public transportation closures, and mandatory wearing of PPE. We identify and code national and subnational public health policies for each subnational unit in 64 countries (subnational aggregates are presently published of USA and Canada only), including countries in North America, Central America, South America, Europe, the Middle East, and Asia. We rely primarily on government resources, press releases, and news sources, dating policies based on first announcement. Note that between and within the policy categories, there is variation on stringency, with some policy adoptions being more stringent than others (i.e. self-isolation versus lockdowns, partial school closings versus full school closings). To this end, we weighed more stringent policies in each category in the index more heavily. Based on coded public health policy responses to COVID-19, we calculate the Public Health Protective Policy Indices (PPI): Regional PPI for each subnational unit on each day; National PPI for a country on each day, based on national level policies; and Total PPI for each subnational unit on each day. The Total PPI reflects the strictest between the national and subnational policies adopted within each category for that unit for that day. The indices are scaled to range between 0 and 1. The Average Total PPI for each country-day is computed by weighing the different units’ Total PPI values by the units’ population shares. The indices apply solely to the measurable subnational and national public-health COVID-19 mitigation policy responses.
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How this classification was reachedexpand
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".