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Record W2963882142 · doi:10.14288/1.0378336

Privacy on social networking sites among Canadian teenagers

2019· article· en· W2963882142 on OpenAlexaboutno aff
Haghighat-Kashani Salma

Bibliographic record

VenuecIRcle (University of British Columbia) · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicPrivacy, Security, and Data Protection
Canadian institutionsnot available
Fundersnot available
KeywordsInternet privacyComputer securityInformation privacyComputer scienceBusiness

Abstract

fetched live from OpenAlex

The widespread popularity of social networking sites (SNSs) among teenagers continually raises concerns over their safety among parents, educators, and policy makers. Although a teen's use of such platforms plays a vital role in his or her social development, such online activities lead to a plethora of personal information being shared that increases vulnerability to privacy invasion and information misuse. The employed monitoring, restriction and educational methods of privacy protection have been unsuccessful in encouraging teens to stay private on SNSs. While researchers have investigated online practices of teens, we lack a clear understanding of the rationales behind their safety and confidence on SNSs. Additionally, with the rapid emergence of new social networking applications each year and the ongoing evolution of educational school programs on privacy, a teen's notion of privacy and online behaviours are constantly evolving. As a result, a thorough exploration of online interactions and thought processes of teens can help us better understand them and consequently communicate with them. This thesis explores the perception of online privacy by Canadian teenagers (15-17 year olds) as well as their privacy-related concerns and behaviours on SNSs. To this end, semi-structured interviews were conducted with high school students (N = 20), and an online survey was completed by a more diverse pool of participants (N = 94). Based on our results, we grounded a theory that highlights our participants' broad definition of online privacy which directly relates to their online privacy concerns. These concerns shape their decision-making processes about information disclosure. Our theory highlights our participants' frequently used rationales for feeling safe online, the variety of protective measures used to address their privacy concerns, and the factors that influence their choice of SNSs. Our findings can help parents and educators gain a better understanding of a teen's perception of online privacy and interactions on SNSs. Additionally, our findings can inform the creation of better suited policies, educational approaches, and parental supervision techniques for teens.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.622
Threshold uncertainty score0.958

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 studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.017
GPT teacher head0.210
Teacher spread0.193 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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