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Record W4413301994 · doi:10.25071/2292-6739.256

Issues of Nationality within Online Spaces: Online Live Streaming Platforms

2025· article· en· W4413301994 on OpenAlexaffvenue
Lorenzo Serravalle

Bibliographic record

VenueContingent Horizons The York University Student Journal of Anthropology · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Culture and Media Studies
Canadian institutionsYork University
Fundersnot available
KeywordsNationalityComputer scienceInternet privacyWorld Wide WebGeographyImmigrationArchaeology

Abstract

fetched live from OpenAlex

This ethnographic report offers insights into the understanding of online communities through the study of the concept of the nation, as discussed by Benedict Anderson (2006). Ethnographic research explores the narratives of nationality that are experienced within an online community that is associated with the practice of online live streaming. This paper also discusses anthropological and non-anthropological methodologies and their importance and usability online. Interaction with interviewees brought to light an understanding of online live streaming as a media product capable of influencing the processes of identity construction in terms of national values. This research thus proves that nations as 'imagined communities' are to be found and analyzed in online communities, where icons such as emotes and memes are used and disseminated as part of the everyday interactions that users undertake in their positions as spectators of live streaming. Nonetheless, this research also struggles with paradoxical understandings of online nationalism, which renders necessary an adaptation to the online setting of established knowledge on the matter.

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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.437
Threshold uncertainty score1.000

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 studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.027
GPT teacher head0.350
Teacher spread0.322 · 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
Published2025
Admission routes2
Has abstractyes

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