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Record W2737222607 · doi:10.1177/1354856517700382

Everyday communication management and perceptions of use

2017· article· en· W2737222607 on OpenAlexaff
Kenzie Burchell

Bibliographic record

VenueConvergence The International Journal of Research into New Media Technologies · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIdeologySocial mediaNegotiationReflexivitySociologyInterpersonal communicationContext (archaeology)PerceptionSet (abstract data type)Divergence (linguistics)EntertainmentBridge (graph theory)Everyday lifePublic relationsSocial psychologyPsychologyComputer sciencePolitical scienceCommunicationPoliticsSocial science

Abstract

fetched live from OpenAlex

For media users enjoying a context of near constant connection across a changing set of platforms, the management of that communication environment is a central concern in the management of everyday life. The multiplication and divergence of possible uses across these platforms emerge alongside the increasing cross-media integration of informational, interactive and entertainment practices with interpersonal communication. The individual’s perception of that environment of increasingly differentiated communication possibilities becomes a site for managing and partially negotiating the limits, form and organization of one’s social world. Expanding upon Gershon’s (2010) notion of media ideologies, this article focuses on the increasing divergence of the perceived and preferred uses of media technologies. The analytical terms ‘social tool’ and ‘social device’ are deployed to tease apart the central ordering experience of perceived ‘mutual engagement’ within media practices. The perceived presence or lack thereof within such engagement serves to recursively delimit and order the media user’s social landscape, pointing to further reflexive management of one’s own media ideology through a highly idiosyncratic ‘relational ordering’ of perceived and preferred platform uses, amidst social and technological change.

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)0.002
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.265
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0030.001
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 head0.155
GPT teacher head0.465
Teacher spread0.310 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
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

Citations11
Published2017
Admission routes1
Has abstractyes

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