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Record W2776614993 · doi:10.20897/jcasc/80926

The Cumulative Disadvantages of Socially Toxic Family Environments: A Comparison of Early Life Experiences of Incarcerated Men and University Students

2017· article· en· W2776614993 on OpenAlexaff
Joseph H. Michalski

Bibliographic record

VenueJournal of Cultural Analysis and Social Change · 2017
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsThe King's University
Fundersnot available
KeywordsFocus groupPsychologyPsychological resilienceQualitative researchDevelopmental psychologyClinical psychologySocial psychologySociology

Abstract

fetched live from OpenAlex

The paper examines the antecedents of criminal behavior through the process of retrospective family and life course histories in which incarcerated male inmates and male university students are compared. The main focus is on early childhood experiences and parental behaviors. The study data derive from intensive, face-to-face interviews with 38 men incarcerated for violent offences and a matched group of 66 men attending university at the same time. The interviews focus on the relative importance of adverse childhood experiences and linkages with adolescence. The interviews demonstrated that nearly four-fifths of the inmates experienced toxic family environments by the time they reached adolescence, as compared with only two of the university students. Qualitative analyses flesh out the major themes, experiences, and “risk factors” that helped shape the trajectories of both groups of men. The socially toxic family environments and sub-optimal parenting practices that most inmates endured produced long-term, adverse effects in reducing their capacities for resilience, forging healthy relationships with their peers, and remaining in school.

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 score0.366
Threshold uncertainty score0.298

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 communication0.0000.000
Open science0.0000.000
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 head0.077
GPT teacher head0.380
Teacher spread0.303 · 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
Published2017
Admission routes1
Has abstractyes

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