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Record W3154144858

The Lived Experience of Families With Children Who Have Sexually Offended in Canada

2021· dissertation· en· W3154144858 on OpenAlexaboutno aff
Amy S. Patterson

Bibliographic record

VenueNational University System Repository (National University System) · 2021
Typedissertation
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyDevelopmental psychologyGenealogyGender studiesMedicineHistorySociology
DOInot available

Abstract

fetched live from OpenAlex

Families with children who have sexually offended are often left to endure an issue that is heavily stigmatized among society. Research on the impact faced by families with children who have sexually offended is significantly limited. Overall, children who sexually offend are a heterogeneous population (Falligant et al., 2017; Fox & DeLisi, 2018). Based on the epidemiology of child sexual abuse, child sexual abuse of younger children is described as rather common, non-enduring, and often driven by factors that can be addressed by prevention efforts (Letourneau et al., 2017). Despite the noted heterogeneity within this population, the research efforts have historically been reductionist. A phenomenological method was used to answer the question: What is the lived experience of families with children who sexually offended in Canada? The findings indicated that the lived experience is distressing, it breaks and reshapes family dynamics, it evokes concerns for the child’s mental health and future, it involves navigating uncomfortable conversations, stigma, and lack of support. These findings are discussed in relation to the current literature.

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)0.007
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 score0.095
Threshold uncertainty score0.693

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0340.013
Scholarly communication0.0070.002
Open science0.0020.006
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.011
GPT teacher head0.225
Teacher spread0.214 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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Same venueNational University System Repository (National University System)Same topicCriminal Justice and Corrections AnalysisFrench-language works237,207