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Record W2626004727 · doi:10.4000/belphegor.1017

Quality Sells

2017· article· fr· W2626004727 on OpenAlexvenueno aff
Ryanne Keltjens

Bibliographic record

VenueBelphégor · 2017
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial and Cultural Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsMiddlebrowSociologyContext (archaeology)Literary criticismField (mathematics)Symbolic capitalLiterary theoryQuality (philosophy)Literary scienceMedia studiesAestheticsLiteratureHistorySocial scienceEpistemologyArtPhilosophy

Abstract

fetched live from OpenAlex

With the emergence of an international bestseller culture in the first half of the twentieth century, foreign literary works were of increasing importance in domestic conceptions of cultural hierarchies. This was in particular the case in peripheral literary systems, which largely depended on translations of foreign novels to meet the growing demands for literary works in this period. Using the international bestsellers Gone with the Wind (1936) by the American author Margaret Mitchell and Katrina (1936) by the Finnish author Sally Salminen as case studies, this article aims to investigate how such works were adapted, marketed and evaluated in the peripheral Dutch literary field of the late thirties. Analyzing publishers’ production and marketing strategies on the one hand and the evaluating practices of literary reviewers on the other, an overview is presented of the ways in which different aspects of this upcoming international bestseller culture influenced the Dutch literary field, focusing in particular on the incorporation of these international bestsellers into local debates. The concept of middlebrow is used within the framework of Bourdieu’s field theory to study mechanisms of cultural distinction and the attribution of symbolic capital to these foreign works in the context of a national literary field.

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)0.002
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: Other · Consensus signal: Other
Teacher disagreement score0.227
Threshold uncertainty score0.761

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0050.002
Scholarly communication0.0150.006
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.2270.052

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 head0.095
GPT teacher head0.401
Teacher spread0.306 · 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
GenreOther

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
Published2017
Admission routes1
Has abstractyes

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