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Record W2571457398 · doi:10.1163/15691330-12341406

Honor and Human Rights: A Comparative Study of Russia and Ukraine

2016· article· en· W2571457398 on OpenAlex
Антон Олейник

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueComparative Sociology · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicLaw in Society and Culture
Canadian institutionsMemorial University of Newfoundland
FundersBard College
KeywordsDignityHonorUkrainianHuman rightsContext (archaeology)Interpretation (philosophy)Political scienceDescriptive statisticsSociologyLawGeographyLinguisticsStatisticsPhilosophyMathematics

Abstract

fetched live from OpenAlex

This article discusses the relative importance attached to honor and human rights in two cultures, Russian and Ukrainian. These cultures have elements of honor cultures, both historically and in the present. There are also elements of a more universalistic interpretation of human dignity that are expressed through the concept of human rights, especially in the case of Ukraine. However, the movement towards the universalistic understanding of human dignity slows down or may even be reversed in the context of a protracted war. Two sources of data inform the analysis: primary (two surveys conducted on representative samples in Russia, N = 1602, and Ukraine, N = 2020) and secondary (the complete works of two poets considered representative of the two cultures, A. Pushkin and T. Shevchenko, as well as documents in the Russian-language and Ukrainian-language segments of the Google online databank). The data were processed using methods of descriptive statistics, binary statistic regression and quantitative content analysis.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.215
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.004
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.085
GPT teacher head0.398
Teacher spread0.314 · 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