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Record W4385563242 · doi:10.1386/jaac_00049_1

Instagram – ‘bringing you closer to the things you love’: Ghanaian popular dance circulation through interaction within current pervasive media

2023· article· en· W4385563242 on OpenAlexaff
Benedictus Mattson

Bibliographic record

VenueJournal of Arts & Communities · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsQueen's University
Fundersnot available
KeywordsDanceGlobalizationPopular cultureSociologyMedia studiesSocial mediaSpace (punctuation)Bridging (networking)AestheticsVisual artsArtPolitical scienceComputer science

Abstract

fetched live from OpenAlex

The advent of social networking today is bringing us closer to the people, places and things we love to see. As an avenue for bridging the communication gap and advancing human interaction, social media’s pervasiveness has had tremendous impact on Ghanaian dance culture in contemporary times. Popular dancers today present their oeuvres in the form of short videos (mostly a minute) on Instagram and solicit user responses from audience of diverse backgrounds and locations. Considering this influence of globalization, its pervasive global communication media, and the move from in-person to virtual communication, it is imperative to interrogate the utilization of the social media networks (especially Instagram) by Ghanaian popular dancers in recent times as regards its impact on the proliferation of the locally created popular dances. This article is framed within the concept of Active and Affective modes of engaging with mediated dances and Connective Marginalities in addition to perspectives from globalization, social media and popular dance studies. Through the analysis of the exploits of two famous popular dancers in Ghana and specific ‘cypher pages’, I highlight the opportunities offered by Instagram as an alternative ‘cultural space’ for the marginalized youth to exhibit their creative ingenuities whilst interacting and reaching out to a wider audience within the shared mediated space.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.591
Threshold uncertainty score0.372

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.001
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 head0.088
GPT teacher head0.348
Teacher spread0.260 · 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.

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
Published2023
Admission routes1
Has abstractyes

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