MétaCan
Menu
Back to cohort
Record W3003218103 · doi:10.5210/spir.v2018i0.10482

NAVIGATING NETWORKED TIME: VISUAL SELF-IDENTITY CONSTRUCTION AND MANAGEMENT AMONG YOUTH

2020· article· en· W3003218103 on OpenAlexaff
Michelle Gorea

Bibliographic record

VenueAoIR Selected Papers of Internet Research · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsQueen's University
Fundersnot available
KeywordsIdentity (music)SociologyVisual researchSocial mediaResource (disambiguation)Everyday lifeKey (lock)SelfSocial psychologyPsychologyPublic relationsAestheticsPolitical scienceComputer scienceVisual artsArt

Abstract

fetched live from OpenAlex

According to dominant theorizations of contemporary society, many people’s daily practices now occur within, and reproduce, a social world where media are the fundamental reference and resource for the development of the self (Couldry and Hepp 2017:15). Although previous research has revealed the mutual shaping of technologies, interaction, and identity in the broader contexts of economic and social change related to ‘millennials’, we know little about the precise ways in which these practices occur and how the self is being differently constructed over time. Using a multi-method qualitative approach, this work in progress paper explores three key questions: 1) What happens when visuality becomes a part of youth’s everyday practices of interaction? 2) What roles are images playing in routine interaction among youth? 3) How and in what ways does the maintenance of a visually ‘mediated presence’ in social media shape youths’ views of the self? This paper elaborates on findings within three categories that illustrate youth’s visual practices and how they are differently understood over time: (1) images of the self in the moment; (2) images of the self over time; and (3) images of the self under surveillance. The preliminary findings of this research suggest that although youth’s technological practices may not all be new, there are significant aspects of visuality that alters some of the key factors shaping young people’s use and understandings of new media technologies.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.231
Threshold uncertainty score0.505

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.025
GPT teacher head0.363
Teacher spread0.338 · 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.

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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueAoIR Selected Papers of Internet ResearchSame topicImpact of Technology on AdolescentsFrench-language works237,207