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Record W3026066346 · doi:10.1075/ld.00059.kat

Is dialogue addictive?

2020· article· en· W3026066346 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.

Bibliographic record

VenueLanguage and Dialogue · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsDialogical selfDialogicExtant taxonAddictionEpistemologyEmpirical researchPsychologySociologyPerspective (graphical)Social psychologyComputer scienceNeuroscience

Abstract

fetched live from OpenAlex

Abstract In this study, we shed some light on the thinking behind Facebook addiction. Since social network system are dialogical communication tools, we carve out a space for a theoretical and methodological alternative to the research on social media addiction, as it relates specifically to Facebook addiction. Based on several meta-evaluations and synthesis of extant empirical research, we uncover the two most prominent functionalist approaches sustaining these empirical researches. Upon pointing to their epistemological, theoretical and methodological limitations, we delve into dialogic approach and theory with a view to isolate how and what it is in a dialogic communication that makes it addictive. Finally, we offer some theoretical and methodological alternatives from a dialogical perspective on how to study Facebook addiction.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.474
Threshold uncertainty score0.499

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.021
GPT teacher head0.295
Teacher spread0.273 · 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