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Record W6999237275

The Changing Landscape of Border Crossing Documents

2020· article· en· W6999237275 on OpenAlexaboutno aff

Bibliographic record

VenueWestern CEDAR (Western Washington University) · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Nexus (standard)LicenseState (computer science)Divergence (linguistics)Border crossing
DOInot available

Abstract

fetched live from OpenAlex

This Border Policy Brief examines the topic of border crossing documents in the context of policy changes at different scales, including provincial, state, and U.S. federal approaches. Specifically, it examines the upcoming implementation of the REAL ID Act in the U.S., the growing elimination of Enhanced Driver’s License programs in Canada, and disruptions to the NEXUS program. It provides an overview of the effects these policy shifts may have on the types of documents used to cross the Canada – U.S. border, using Blaine, Washington as an example. The Brief explores the importance of different ID types and their capabilities, as well as a growing divergence between state and federal programs within the U.S., both of which impact the efficiency and security of the Canada – U.S. border.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.470
Threshold uncertainty score0.946

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.025
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0060.011
Science and technology studies0.0250.029
Scholarly communication0.0380.015
Open science0.0020.007
Research integrity0.0060.008
Insufficient payload (model declined to judge)0.0080.001

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 head0.020
GPT teacher head0.273
Teacher spread0.253 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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
Published2020
Admission routes1
Has abstractyes

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