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Record W1582915330 · doi:10.20355/c5g59s

From Segregation to Equalization: The Polish Perspective

2007· article· en· W1582915330 on OpenAlexaffvenue
Małgorzata Gil

Bibliographic record

VenueJournal of Contemporary Issues in Education · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicCollaborative Teaching and Inclusion
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsLegislationSpecial educationNorm (philosophy)UnderpinningPerspective (graphical)Political sciencePedagogyPostsecondary educationPsychologyEconomic growthMedical educationHigher educationMedicineLawEconomics

Abstract

fetched live from OpenAlex

Previously in Poland, the segregation of children with disabilities was the norm. Recent changes to legislation entitled “Equalization of Opportunities for Persons with Disabilities” specifically address the education of persons with disabilities. States are required to recognize the principle of equal primary, secondary and tertiary educational opportunities for children, youth and adults with disabilities into integrated settings. The education of persons with disabilities should be an integral part of the educational system (United Nations, 1993). This article reports on the education of children with intellectual disabilities living in full-time care institutions and provides an analysis of assumptions underpinning inclusive education in Poland. Specifically, this paper will: (a) introduce the history of education for children with disabilities, (b) provide an analysis of current legislation from 1991 to 2003 addressing education for children with disabilities, and, (c) explore examples of how education was provided to a select group of institutionalized children and young adults. In spite of recent changes to educational policy and formal regulations within the educational system, students with intellectual disabilities continue to be segregated within educational institutions.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.023
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0090.024
Scholarly communication0.0120.013
Open science0.0010.012
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0040.001

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 head0.032
GPT teacher head0.425
Teacher spread0.393 · 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 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

Citations3
Published2007
Admission routes2
Has abstractyes

Explore more

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