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Being a good digital parent: representations of parents, youth and the parent–youth relationship in expert advice

2021· article· en· W3145938758 on OpenAlexaff
Glenda Wall

Bibliographic record

VenueFamilies Relationships and Societies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsAgency (philosophy)PsychologyJudgementDevelopmental psychologyContext (archaeology)Face (sociological concept)Social psychologySociologyPolitical science

Abstract

fetched live from OpenAlex

Social concern about online behaviour and safety of children and youth has increased dramatically in the last decade and has resulted in an abundance of parenting advice on ways to manage and protect children online. The cultural context in which this is happening is one characterised by intensive parenting norms, heightened risk awareness, and growing concerns about the effects of ‘over-parenting’, especially in the teenage years. Using contemporary advice to parents on managing adolescents’ digital experiences, this study investigates the ways that parenting, youth and the youth–parent relationship are depicted. Parental roles, in this material, are portrayed as instrumental and pedagogical while youth are assumed to lack agency and judgement. Intensive parenting expectations are extended as parents face advice to be both highly vigilant agents of surveillance and trusted confidantes of their children, with an overall goal of shaping children’s subjectivity in ways that allow them to become self-governing.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.005
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0010.002
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 head0.051
GPT teacher head0.288
Teacher spread0.237 · 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 designQualitative
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

Citations15
Published2021
Admission routes1
Has abstractyes

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