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Record W2553056477

Translation and Community-building for Transnational Learning in Cuba and Russia

2016· article· en· W2553056477 on OpenAlexaboutno aff
Anne A. Macpherson, Barbara LeSavoy

Bibliographic record

VenueSUNY Digital Repository Support (State University of New York System) · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicHistory, Medicine, and Leadership
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceEconomic growthEconomics
DOInot available

Abstract

fetched live from OpenAlex

Anne Macpherson, PhD, is a member of Brockport's History faculty. Raised in Canada, she did French immersion and then studied Spanish intensively in Costa Rica. A specialist in 20th century Caribbean political, gender, and labor history, she has done research in Belize and Puerto Rico. Her book on Belizean women's history won the Association of Caribbean Historians' (ACH) book prize in 2008. Her book on New Deal labor reform in Puerto Rico, 1937-41, is nearing completion. She teaches modern world/food history, Latin American, and Caribbean history. She has attended ACH conferences in Jamaica, Puerto Rico, Belize, and most recently Cuba.\nBarbara LeSavoy, PhD, is Director of Women and Gender Studies at Brockport and teaches Global Perspectives on Women and Gender among other classes. She researches women’s global human rights, sex and gender in literature and popular culture, intersectionality and educational equity/success, and women’s stories as feminist standpoint. She has founded two journals, serves as lead faculty for a Collaborative Online International Learning project linking students at Brockport and Novgorod State University in Russia and teaches a summer Women and Gender Studies Seminar at the NY Institute of Linguistics, Cognition, and Culture at St Petersburg University in St. Petersburg, Russia.

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)0.004
metaresearch head score (Gemma)0.005
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: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.003
Scholarly communication0.0070.004
Open science0.0010.010
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0170.002

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 head0.040
GPT teacher head0.242
Teacher spread0.202 · 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
Published2016
Admission routes1
Has abstractyes

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