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Record W2592160520

Special Education Instruction in the Jewish Ultra Orthodox and Hassidic Communities in Toronto

2012· dissertation· en· W2592160520 on OpenAlexaboutno aff
Marcus Benayon

Bibliographic record

VenueTSpace · 2012
Typedissertation
Languageen
FieldSocial Sciences
TopicJewish Identity and Society
Canadian institutionsnot available
Fundersnot available
KeywordsJudaismSociologyReligious studiesPedagogyHistoryArchaeologyPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

The purpose of the present study was to examine the state of special education programs in selected Jewish Ultra Orthodox (Haredi) community schools in the Greater Toronto Area (GTA), and the attitudes and perceptions about special education of the Melamdim (rabbis/teachers) teaching in those schools. A Special Education course, modeled on OISE’s additional qualification program available to in-service teachers in the public sector, was administrated to 28 Melamdim. Throughout the 12 weeks, course data was collected through observations and dialogues with course participants. The impact of the special education course on classroom practices by those who engaged in the course was also assessed. In addition, a collection of pre-course and post-course data from participants (Melamdim) on attitudes and perceptions in regards to special education through a self-administrated questionnaire, took place. Four additional questionnaires were administered, examining demographic characteristics, general attitudes and behaviors, and well-being. Finally, a pre-selected group of 8 Melalmdim was interviewed as representatives of their home school and the denomination of Judaism they belong to. The results showed significant changes in attitudes of Melamdim toward the inclusion of students with Learning Disabilities (LD in regular classrooms. In addition, the positive change in attitudes could be attributed to the special education course in which participants engaged. During in-class observations changes to the Melamdim’s own practice was recorded.

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)0.001
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.594
Threshold uncertainty score0.672

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.032
GPT teacher head0.371
Teacher spread0.339 · 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 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

Citations1
Published2012
Admission routes1
Has abstractyes

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