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Record W3136163968 · doi:10.1080/13876988.2021.1894073

Utilizing a Comparative Policy Resource from the WORLD Policy Analysis Center Covering Constitutional Rights, Laws, and Policies across 193 Countries for Outcome Analysis, Monitoring, and Accountability

2021· article· en· W3136163968 on OpenAlex
Amy Raub, Aleta Sprague, Willetta Waisath, Arijit Nandi, Efe Atabay, Ilona Vincent, Gonzalo Moreno, Alison Earle, Nicholas Perry, Jody Heymann

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Comparative Policy Analysis Research and Practice · 2021
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsMcGill UniversityMcGill University Health Centre
FundersWilliam and Flora Hewlett FoundationConrad N. Hilton FoundationBill and Melinda Gates FoundationFord Foundation
KeywordsAccountabilityPovertyPolicy analysisSocioeconomic statusPolitical sciencePublic administrationOutcome (game theory)Public economicsPublic policyEconomicsLawSociologyPopulation

Abstract

fetched live from OpenAlex

Historically, a lack of comparable data on the laws and policies that shape health, education, poverty, and other outcomes has hindered researchers’ ability to provide rigorous evidence on the effectiveness of different policy designs. This article describes public-use downloadable data built by the WORLD Policy Analysis Center to fill this gap. Over 2,000 quantitatively comparable measures of national laws and policies across 193 countries were assembled. This open-access data source provides a tool for monitoring the adoption of evidence-based laws and policies, identifying policy gaps, and rigorously evaluating how policies shape outcomes across different regions and socioeconomic contexts.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.289
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.010
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.191
GPT teacher head0.535
Teacher spread0.344 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it