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Record W4291583390 · doi:10.32674/jcihe.v14i2.4901

JCIHE Volume 14(2) Introduction

2022· article· en· W4291583390 on OpenAlexaboutno aff
Rosalind Latiner Raby

Bibliographic record

VenueJournal of Comparative & International Higher Education · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Educational Policies and Reforms
Canadian institutionsnot available
Fundersnot available
KeywordsScholarshipContext (archaeology)Political scienceHigher educationCoronavirus disease 2019 (COVID-19)ChinaEditorial boardInternational educationLibrary sciencePublicationMedia studiesSociologyHistoryLawMedicine

Abstract

fetched live from OpenAlex

I am pleased to share Volume 14, Issue 2, 2022 of the Journal of Comparative and International Higher Education (JCIHE). In this current issue JCIHE is honored to publish articles of higher education on the following countries: Azerbaijan, Barbados, Canada, China, Hungary, Iraq, Tajikistan, Taiwan, United Kingdom, and United States. JCIHE publishes new and emerging topics in comparative and international higher educational whose themes represent scholarship from authors from around the world. Two broad themes are represented in the articles in the 14(2) Issue: Student Learning Strategies and Institutional Context. For this issue, the Editorial Board invited two high-profile internationalists: Allan Goodman, of the Institute of International Education and Mirka Martel of the Institute of International Education to write a reflective essay about the effects of COVID-19, on student mobility. They focus on changes between the different waves of COVID-19 and projections for the future. We conclude this issue with a Book Review by Sneha Bhasin.

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)0.003
metaresearch head score (Gemma)0.010
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.187
Threshold uncertainty score0.626

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0030.002
Scholarly communication0.0120.004
Open science0.0010.003
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.1870.080

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 head0.029
GPT teacher head0.388
Teacher spread0.359 · 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
GenreEditorial

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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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