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Record W38896447 · doi:10.2196/51498

Between National and Academic Agendas : Ethnic Policies and ‘National Disciplines’ at the University of Latvia, 1919–1940

2012· article· en· W38896447 on OpenAlexvenueno aff
Per Bolin

Bibliographic record

VenueJMIR Public Health and Surveillance · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical Geopolitical and Social Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsEthnic groupPolitical sciencePublic administrationNational PolicyEconomic growthEconomicsLaw

Abstract

fetched live from OpenAlex

How was the national agenda of a previously subordinated, ruling Latvian majority reconciled with established academic practices for appointments and enrolment – candidates judged on merit irrespective of ethnicity? Following the disintegration of the Russian Empire, the ethnic Latvian majority assumed power and used state resources to further their national project. Complex national issues arose when a new university, teaching in Latvian, was founded in 1919 – Latvian was a language previously regarded as a peasant vernacular wholly unsuitable for cultural or academic purposes. During the same period the Latvian state was a multi-ethnic parliamentary democracy containing several ethnic minorities, all with full citizenship rights. Some of these minorities, the Baltic Germans and the Jews in particular, possessed considerable cultural capital and experience of academia. The inherent conflicts and compromises in this double agenda are the main focus of Between National and Academic Agendas.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0090.003
Scholarly communication0.0030.001
Open science0.0000.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.094
GPT teacher head0.383
Teacher spread0.289 · 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

Citations22
Published2012
Admission routes1
Has abstractyes

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