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Record W6926538129 · doi:10.25316/ir-15136

Quality IEP development, implementation and progress monitoring aligned to Ontario provincial polices

2020· dissertation· en· W6926538129 on OpenAlexaboutno aff

Bibliographic record

VenueVIURRSpace (Vancouver Island University) · 2020
Typedissertation
Languageen
FieldMedicine
TopicMicrobial Natural Products and Biosynthesis
Canadian institutionsnot available
Fundersnot available
KeywordsQuality (philosophy)Plan (archaeology)Gateway (web page)Special educationProfessional developmentIndividualized Education Program

Abstract

fetched live from OpenAlex

Every student deserves the right to a quality education. For an individual with special education needs, the Individual Education Plan (IEP) is the gateway to a quality education. Pre-service and in-service teachers believe that they are inadequate at supporting students with special education needs and require professional development to gain the knowledge and skills to effectively engage in the IEP process. This project explores the essential components teachers require to effectively engage in the IEP process; specifically, in the development, implementation and progress monitoring of quality IEPs. The IEP Guide for Educators has been developed to aid educators to effectively use the IEP as a functional tool in planning, implementing, monitoring and reviewing educational practices to provide meaningful enriched educational experiences for the most vulnerable student population, individuals with special education requirements.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.578
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.017
GPT teacher head0.275
Teacher spread0.258 · 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.

Study designNot applicable
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
Published2020
Admission routes1
Has abstractyes

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