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Record W7108318127 · doi:10.3886/e240869v1

HIFLD OPEN North America Political Divisions Polygons

2025· dataset· en· W7108318127 on OpenAlexaboutno aff

Bibliographic record

VenueICPSR Data Holdings · 2025
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsGeospatial analysisAtlas (anatomy)Context (archaeology)State (computer science)Political geographyThematic mapCommission

Abstract

fetched live from OpenAlex

The North American Atlas data are standardized geospatial data. A variety of basic data layers (e.g. roads, railroads, populated places, political boundaries, hydrography, bathymetry, sea ice and glaciers) have been integrated so that their relative positions are correct. This collection of data sets forms a base with which other North American thematic data may be integrated. Any data outside of Canada, Mexico, and the United States of America included in the North American Atlas data sets is strictly to complete the context of the data.The new version of the North American Atlas - Political Boundaries data set shows political entities in North America as polygons representing jurisdictional areas, such as, International boundaries, Provincial boundaries and State or territory boundaries.This is a revised version of the 2010 data set released by the Commission for Environmental Cooperation. This new version integrates political boundaries spatial vector information published by each country in 2021. The data set includes 10 provinces and 3 territories in Canada; 32 states in Mexico; 48 states and the District of Columbia in the conterminous United Sates, Alaska and Hawaii, as well as Puerto Rico and the US Virgin Islands in the Caribbean region.Files Download

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 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)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Open science, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.028
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0280.049
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.012

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 head0.079
GPT teacher head0.385
Teacher spread0.306 · 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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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Same venueICPSR Data HoldingsFrench-language works237,207