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Record W2330478345 · doi:10.1386/ajms.4.1.3_1

Media in minority contexts: Towards a research framework

2015· article· en· W2330478345 on OpenAlexaffabout
Élisabeth Le

Bibliographic record

VenueJournal of Applied Journalism & Media Studies · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicTranslation Studies and Practices
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMultidisciplinary approachTheme (computing)Perspective (graphical)SociologySociocultural evolutionPolitical scienceField (mathematics)Public relationsMedia studiesEngineering ethicsSocial scienceComputer scienceEngineeringLaw

Abstract

fetched live from OpenAlex

Abstract This special issue on ‘Media in minority contexts’ includes some of the best papers presented at a 2012 conference on the same theme held at the University of Alberta. The issue comprises as well three articles written by media practitioners in response to the researchers’ work. It also provides a general literature review of the field distinguishing two main strands of research: the status of media in minority contexts, and the participation of minorities in national, transnational and international debates. This second strand can itself be divided into three different subfields: cultural representations, communicative structures and sociocultural conditions for media access and use. The first article is an introduction to the special issue. It underlines how each of the articles in this special issue adds to the two strands and their subfields. It lays out some questions to explore further and argues that the research framework thus outlined ought to be considered from a multidisciplinary perspective.

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)0.027
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.031
Threshold uncertainty score0.144

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0130.010
Science and technology studies0.0090.035
Scholarly communication0.0310.030
Open science0.0040.014
Research integrity0.0070.006
Insufficient payload (model declined to judge)0.0040.001

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 head0.307
GPT teacher head0.421
Teacher spread0.113 · 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 designTheoretical or conceptual
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

Citations3
Published2015
Admission routes2
Has abstractyes

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