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Record W4323899078 · doi:10.1123/ijsc.2023-0001

Habitually Scrolling: An Examination Into How Sport Consumers Use Social Media

2023· article· en· W4323899078 on OpenAlexaff
Heather Kennedy, Daniel C. Funk

Bibliographic record

VenueInternational Journal of Sport Communication · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsUnconscious mindSocial mediaPsychologyAdvertisingUses and gratifications theorySocial psychologySociologyBusinessPolitical science

Abstract

fetched live from OpenAlex

Uses and gratifications theory has often been used in (sport) communication studies to examine social media usage. Yet, criticisms of uses and gratifications theory (e.g., it overstates purposefulness) and competing research suggesting media use is more habitual and unconscious in nature have often been overlooked. Thus, through semistructured interviews, this research explored how social media is used, identifying five themes: passively, distinctly, periodically, habitually, and universally. Theoretically, this research contributes by highlighting the passive, habitual, and unconscious nature of some sport social media behavior, thereby challenging our current assumptions that sport social media usage is always active, purposeful, and goal directed. It also considers the uniqueness (or lack thereof) of sport content within the social media experience. Managerially, this research helps sport organizations understand how consumers use social media to inform marketing and communication strategies.

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)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0020.003
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.080
GPT teacher head0.354
Teacher spread0.274 · 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 designObservational
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

Citations14
Published2023
Admission routes1
Has abstractyes

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