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Record W7025164390

Understanding perceptions of social relationships with children among pedohebephilic individuals : a two-part study

2023· article· en· W7025164390 on OpenAlexaff

Bibliographic record

VenueSaint Mary's University Institutional Repository (Saint Mary's University) · 2023
Typearticle
Languageen
FieldComputer Science
TopicCloud Computing and Resource Management
Canadian institutionsTechnical University of Nova Scotia
Fundersnot available
KeywordsSocial relationshipPerceptionSocial relationInterpersonal relationshipAffect (linguistics)Perspective (graphical)
DOInot available

Abstract

fetched live from OpenAlex

The current thesis comprises two studies examining social relationships with children among pedohebephilic individuals.Study one quantitatively examined mediators (i.e., internalized stigma, loneliness, sexual fantasies) of the association between social relationships with children, suicide, and a history sexual offending.Study two qualitatively explored reasons pedohebephilic individuals seek social relationships with children, and how these social relationships are conceptualized.Study one results did not demonstrate either partial or full mediation.Despite this, the length of social relationships with children was associated with a history of sexual offending.Results from qualitative study two noted four themes that highlighted concerns of dynamic changes, emotional congruence with children, challenges and risk of relationships with children, and the role of social networks.Findings suggest emotional congruence with children, social isolation from adults, and one's social network are likely to be contributing factors for pedohebephilic individuals developing social connections with children.August 28 th , 2023 To my supervisor, Dr. Skye Stephens, thank you for the time and effort you put into me and my growth as a researcher and aspiring clinician.Over the past two years you have given me the guidance, support, and confidence needed to start

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.422
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0040.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.032
GPT teacher head0.208
Teacher spread0.176 · 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 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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueSaint Mary's University Institutional Repository (Saint Mary's University)Same topicCloud Computing and Resource ManagementFrench-language works237,207