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Record W4415767488 · doi:10.1080/17440572.2025.2579992

Exploring the prevalence and correlates of identity theft-related preventive measures among U.S. adolescents

2025· article· en· W4415767488 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGlobal Crime · 2025
Typearticle
Languageen
FieldComputer Science
TopicCybercrime and Law Enforcement Studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsIdentity (music)Social identity theoryQualitative researchVariation (astronomy)Mental health

Abstract

fetched live from OpenAlex

Adolescents represent an emerging population at risk of identity theft, yet little is known about their engagement in preventive behaviours. Using data from a nationally representative sample of U.S. adolescents who participated in the National Crime Victimization Survey – Identity Theft Supplement (NCVS-ITS), this study examined the prevalence of six identity theft-related preventive behaviours and assessed the influence of demographic and contextual factors on the likelihood of engaging in these practices. Descriptive findings revealed low overall adoption of preventive behaviours, even among adolescents with financial accounts. Logistic regression analyses indicated that having a checking/savings account and, to a lesser extent, owning a credit card were the most consistent and significant predictors of engagement in preventive behaviours. Age and household income also emerged as significant predictors in several models, while race, gender, and ethnicity were largely nonsignificant. The implications of the findings are discussed.

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.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.210
Threshold uncertainty score0.377

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 studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.031
GPT teacher head0.269
Teacher spread0.238 · 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