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Record W4233389842 · doi:10.1057/9781137394934.0013

Identity Discourses and Narratives in North Korean Events, Festivals and Celebrations

2015· book-chapter· en· W4233389842 on OpenAlexaff
Udo Merkel, Gwang Ok

Bibliographic record

VenuePalgrave Macmillan eBooks · 2015
Typebook-chapter
Languageen
FieldSocial Sciences
TopicKorean Peninsula Historical and Political Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsNarrativeIdentity (music)HistoryGender studiesGeographyAestheticsGenealogyLiteratureSociologyArt

Abstract

fetched live from OpenAlex

In this book series, we defend leisure as a meaningful, theoretical, framing concept; and critical studies of leisure as a worthwhile intellectual and pedagogical activity.This is what makes this book series distinctive: we want to enhance the discipline of leisure studies and open it up to a richer range of ideas; and, conversely, we want sociology, cultural geographies and other social sciences and humanities to open up to engaging with critical and rigorous arguments from leisure studies.Getting beyond concerns about the grand project of leisure, we will use the series to demonstrate that leisure theory is central to understanding wider debates about identity, postmodernity and globalization in contemporary societies across the world.The series combines the search for local, qualitatively rich accounts of everyday leisure with the international reach of debates in politics, leisure and social and cultural theory.In doing this, we will show that critical studies of leisure can and should continue to play a central role in understanding society.The scope will be global, striving to be truly international and truly diverse in the range of authors and topics.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0090.006
Scholarly communication0.0070.007
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.046
GPT teacher head0.308
Teacher spread0.262 · 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 designQualitative
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
Published2015
Admission routes1
Has abstractyes

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