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Record W4205690996 · doi:10.18778/1733-8077.12.1.05

Expanding Our Methodological Toolbox: The “Place” of Twitter in the Ethnographic Endeavor

2016· article· en· W4205690996 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueQualitative Sociology Review · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsMcMaster University
Fundersnot available
KeywordsToolboxSociologySocial mediaSocial worldsLeagueEthnographyFootballMedia studiesPublic relationsSocial scienceResource (disambiguation)World Wide WebPolitical scienceComputer scienceAnthropologyLaw

Abstract

fetched live from OpenAlex

Social media have been increasingly embraced by social actors inhabiting a wide range of social worlds, including the world of professional sports. This paper argues that Twitter has become an indispensible resource for sociologists seeking to better understand these worlds. Using data collected for a study of the Canadian Football League (CFL), the paper contrasts traditional interviews and Twitter as sources of data. This is followed by a discussion of both the unique advantages and limitations of Twitter data in research. The paper ends by encouraging an expansion of sociology’s methodological toolbox to include this form of social media.

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.

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)0.017
metaresearch head score (Gemma)0.014
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 score0.482
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.562
GPT teacher head0.600
Teacher spread0.038 · 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