MétaCan
Menu
Back to cohort
Record W4291149689 · doi:10.15575/jassr.v4i1.59

Alternative Imaginations: Confronting and Challenging the Persistent Centrism in Social Media-Society Research

2022· article· en· W4291149689 on OpenAlexaff
Merlyna Lim

Bibliographic record

VenueJournal of Asian Social Science Research · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsCarleton University
FundersUniversity of OxfordPennsylvania State UniversityHarvard University
KeywordsSocial mediaNoveltyCentralitySociologyValue (mathematics)Context (archaeology)Social scienceEpistemologyPublic relationsPsychologyPolitical scienceSocial psychologyComputer scienceLaw

Abstract

fetched live from OpenAlex

This article attempts to intervene the current trend in social media research that, to a certain degree, reflects the centrality of technology. Beyond the broad trend of technocentrism, I identify and outline four other major oversights or challenges in researching the social media/society relationship, namely online data centrism, moment centrism, novelty centrism, and success centrism. Stemmed from these four types of centrism, I offer an alternative imagination, namely a set of alternative pathways in social media research that value histories and historical context, interdisciplinarity, longue durée, and complexity. By revealing these oversights, this article aims to contribute to our collective attempt to interrogate the relationship between social media and society (and technology/society) critically. This alternative imagination might help animate, reveal, and make transparent various societal dynamics that otherwise would be invisible and, thus, might contribute to a better, deeper, and more comprehensive understanding of the technology/society relationship.

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)0.038
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.286
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0380.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0150.007
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.003
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 head0.197
GPT teacher head0.494
Teacher spread0.297 · 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; both teacher heads agree on what is shown here.

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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Asian Social Science ResearchSame topicSocial Media and PoliticsFrench-language works237,207