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Record W7026968489

Approval of Biden's Handling of Ukraine Jumps in NH But Many Fear Direct Confrontation With Russia 3/22/2023

2023· article· en· W7026968489 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of New Hampshire Scholars Repository (University of New Hampshire at Manchester) · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean and Russian Geopolitical Military Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsState (computer science)ChinaQuarter (Canadian coin)Foreign policyWorld War IIGovernment (linguistics)Cold warTerritorial integrity
DOInot available

Abstract

fetched live from OpenAlex

A majority of New Hampshire residents approve of how President Joe Biden is handling the war in Ukraine, significantly higher than in the summer of 2022. A plurality expect the war in Ukraine to end with a compromise, while a quarter expect Ukraine to take back all of its territory. Although more than two-thirds of Granite Staters are worried about a direct confrontation between Russia and the U.S. in the near future, state residents consider China to be the greatest foreign threat to the United States by far.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.048
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0090.001
Scholarly communication0.0040.001
Open science0.0000.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0230.006

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 head0.022
GPT teacher head0.226
Teacher spread0.205 · 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 designObservational
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
Published2023
Admission routes1
Has abstractyes

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