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Record W2954869029 · doi:10.1386/joacm_00060_1

Ethnic media as alternative media for South Asians in Metro Vancouver, Canada: Creating knowledge, engagement, civic and political awareness

2019· article· en· W2954869029 on OpenAlexaffabout

Bibliographic record

VenueJournal of Alternative & Community Media · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicMedia Studies and Communication
Canadian institutionsConcordia University
Fundersnot available
KeywordsEthnic groupMainstreamCitizen journalismNewspaperPoliticsMedia studiesGender studiesImmigrationPolitical sciencePopulationSociologyCivic engagementAnthropology

Abstract

fetched live from OpenAlex

South Asians, making 11% of the total population of Metro Vancouver, have established a large number of ethnic media sources including exclusive 24/7 radio stations, several newspapers, magazines, and online media in different South Asian languages for their audience. This qualitative research study of ethnic media of South Asian communities living in Metro Vancouver, reveals that ethnic media, specifically radio, provided active media space for discussion and dialogue on crucial issues concerning their everyday life challenges as ‘immigrant communities’. According to the participants, ethnic media triggered political activism and awareness through their content, especially due to mainstream media’s failure of coverage or negative coverage of ethnic minorities. This qualitative study uses in-depth interviews with thirteen South Asian ethnic media practitioners including media owners, journalists, and anchorpersons, as well as focus group discussions with South Asian audiences in Metro Vancouver. The article discusses the role of South Asian ethnic media, as alternative media, in creating knowledge, engagement, civic and political awareness, and giving a participatory platform to raise the voices of their audiences.

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 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)0.005
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.581
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.108
GPT teacher head0.390
Teacher spread0.283 · 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 teacher head, not a consensus.

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

Citations3
Published2019
Admission routes2
Has abstractyes

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