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Record W2758118682

Navigating Surveillance Discourse: Virtual Space, Childhood, and Contrasting Representations of Online Safety

2014· dissertation· en· W2758118682 on OpenAlexaboutno aff
Ashley Inskip-Lavoie

Bibliographic record

VenueTSpace · 2014
Typedissertation
Languageen
FieldSocial Sciences
TopicCrime, Deviance, and Social Control
Canadian institutionsnot available
Fundersnot available
KeywordsVirtual spaceSpace (punctuation)Computer scienceHuman–computer interactionArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

This project looked at two different sets of data to further understand the relationship between surveillance discourse and the Internet, how surveillance discourse around navigating the Internet has developed, and how children use social technology and digital media for positive communication as well as an alternative space for social engagement. This project argues that there is a disconnect between the way children use social technology, and the approach authoritative websites take in aiming to educate parents, educators, and children on using the Internet safely. This study performs a thematic content analysis on websites that aim to educate on Internet Safety. Additionally, this qualitative study focuses on semi-structured interviews with grade 4-6 students in a French language school in Western Ontario and their reaction to the question, “how do you use technology”. This project is a stepping-stone into many conversations around the possibilities present for the Internet, children, and communication.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.350
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.014
GPT teacher head0.393
Teacher spread0.380 · 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 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

Citations0
Published2014
Admission routes1
Has abstractyes

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