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Record W4386763874 · doi:10.32920/24150426

Re‐Imagining Inclusion Through the Lens of Disabled Childhoods

2023· preprint· en· W4386763874 on OpenAlexaff
Alice-Simone Balter, Laura Feltham, Gillian Parekh, Patty Douglas, Kathryn Underwood, Tricia van Rhijn

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicChildren's Rights and Participation
Canadian institutionsYork UniversityToronto Metropolitan UniversityBrandon UniversityUniversity of Guelph
Fundersnot available
KeywordsInclusion (mineral)Flexibility (engineering)Disability studiesEarly childhoodEthnographyDevelopmental psychologyPsychologySociologyGender studies

Abstract

fetched live from OpenAlex

The purpose of this article is to contribute new insights to critical disability and disabled children’s childhood studies that center on the valuing of disabled children’s lives—a guiding purpose in the disability justice movement. We use published findings from the Inclusive Early Childhood Service System project, a longitudinal, institutional ethnography of the ways that families and children are organized around categories of disability, which show social inclusions and exclusions before and during the pandemic. These findings illuminate: (a) institutional flexibility for the purpose of social inclusion and isola‐ tion during the pandemic as a result of institutional organization; (b) the impact of institutional decisions around closures, remote programs, and support on families’ choices and self‐determination; and (3) the ways safety is differently applied and rationalized for disabled children allowing institutions to exclude disabled children and families. We use critical dis‐ ability studies and disabled children’s childhood studies to interpret these findings and position the valuing of disabled children’s lives with a call for disability justice actions.

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)0.007
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.022
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.002
Science and technology studies0.0130.096
Scholarly communication0.0140.016
Open science0.0010.012
Research integrity0.0020.006
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 head0.110
GPT teacher head0.386
Teacher spread0.276 · 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 designTheoretical or conceptual
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

Citations1
Published2023
Admission routes1
Has abstractyes

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