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The Systemic Invisibility of Children of Prisoners

2018· book· en· W2901091110 on OpenAlexaboutno aff
Else Marie Knudsen

Bibliographic record

VenueOxford University Press eBooks · 2018
Typebook
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsInvisibilitySituatedContext (archaeology)PrisonSubject (documents)CriminologySociologyPopulationPsychologyPolitical scienceGender studiesGeographyDemographyComputer science

Abstract

fetched live from OpenAlex

This chapter argues that the children of prisoners are rendered invisible from the micro to the macro level, through a series of interconnected processes the chapter refers to as ‘systemic invisibility’. This study, moreover, is situated in the Canadian context, particularly in the experiences of Canadian children of prisoners. While these children make up a sizeable population, and the experience and outcomes of parental incarceration appear to be significant, they are often hidden from view, subject to layers of invisibility. Starting from children’s own families, to their relationship with their schools and communities, to the policies and practices of the prison systems in which they are so tightly intertwined, and finally to the broader social policy context, the chapter discusses the ways in which parental incarceration is kept secret, enigmatic, and poorly understood. Finally, the chapter considers the meanings and reasons behind these connected layers of invisibility.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.399
Threshold uncertainty score0.792

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.023
Scholarly communication0.0050.003
Open science0.0010.006
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.018
GPT teacher head0.245
Teacher spread0.228 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations18
Published2018
Admission routes1
Has abstractyes

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Same venueOxford University Press eBooksSame topicCriminal Justice and Corrections AnalysisFrench-language works237,207