MétaCan
Menu
← Back to cohort
Record W4251216477 · doi:10.32920/ryerson.14664303.v1

Maternal incarceration : exploring the impact on children

2021· preprint· en· W4251216477 on OpenAlexaff
Lia Morrin Jenner

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsAffect (linguistics)Exploratory researchPerspective (graphical)PsychologyDevelopmental psychologySociologySocial science

Abstract

fetched live from OpenAlex

The purpose of this exploratory research study was to examine the impact of maternal incarceration on mothers and their children from an ecological perpective. Individual interviews were conducted with four mothers who have previously been in conflict with the law and have been in custody for a minimum twelve months. Two primary workers from Elizabeth Fry Society of Simcoe County were also interviewed for another perspective pertaining to this topic. Participants were recruited by distributing advertisements at the Elizabeth Fry Society of Simcoe County. This study coincided with the literature and found that there are a number of combining factors from the broader system which impact the developmetnal outcomes of a child. After analyzing the data it appeared that there were two main aspects reported by all participants that affect children when their mothers are incarcerated. These include: System Barriers and Resouce Barriers. The participants from this study recommended child friendly centres and physical visitations to rectify and mainain the mother-child relationship while mothers are incarcerated. This study helped to deconstruct norms associated with traditional families and recognized the unique experiences of mother-child relationships during incarceration.

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)0.001
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.056
GPT teacher head0.350
Teacher spread0.293 · 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

Explore more

Same topicCriminal Justice and Corrections Analysis→French-language works237,207→