MétaCan
Menu
Back to cohort
Record W4393031711 · doi:10.14393/dlv18a2024-11

Hashtag como elemento (des)organizador do discurso político

2024· article· pt· W4393031711 on OpenAlexaff
Gustavo Haiden de Lacerda

Bibliographic record

VenueDomínios de Lingu gem · 2024
Typearticle
Languagept
FieldArts and Humanities
TopicCultural, Media, and Literary Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

Este artigo, com base na Análise de Discurso Materialista (AD), discute o modo pelo qual as hashtags (des)organizam os discursos político-midiáticos no X-Twitter. O corpus construído para o presente gesto analítico foi elaborado em torno da hashtag #quemmorreu, desde sua enunciação primeira até suas retomadas em outras vinte e uma publicações. Alicerçado nos postulados metodológicos da AD, o estudo observou as regularidades entre as circulações da hashtag para compreender a estruturação algorítmica de seus efeitos de sentido pela forma como significa os discursos nas redes digitais. As análises levaram à compreensão de um efeito de rumor derrisório, atrelado à forma do discurso polêmico, que desestabiliza poderes políticos e midiáticos estabelecidos, reivindicando outros sentidos pela contenda ideológica algoritmicamente mediada pela disputa acerca de #quemmorreu.

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)0.011
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.019
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.006
Science and technology studies0.0020.002
Scholarly communication0.0050.005
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0190.005

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 head0.026
GPT teacher head0.275
Teacher spread0.249 · 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 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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueDomínios de Lingu gemSame topicCultural, Media, and Literary StudiesFrench-language works237,207