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Policies That Foster Education for All: Implications for Economically Wealthy Nations

2020· reference-entry· en· W3082639531 on OpenAlexaboutno aff
Steve Sider

Bibliographic record

VenueOxford Research Encyclopedia of Education · 2020
Typereference-entry
Languageen
FieldSocial Sciences
TopicDisability Education and Employment
Canadian institutionsnot available
Fundersnot available
KeywordsEconomic growthPolitical sciencePublic relationsSocioeconomic statusInclusion (mineral)PsychologySociologyEconomicsSocial psychologyPopulation

Abstract

fetched live from OpenAlex

Efforts to support education for all students have increasingly become priorities for governments around the world. Key international agreements, including the Sustainable Development Goals and the United Nations Convention on the Rights of the Child, have provided foundational direction to jurisdictions in implementing policies to engage all students including those with special education needs. As initiatives to support equitable and inclusive education for all become more widespread globally, it is important to consider how these efforts affect economically wealthy countries. Using the example of Canada, and specifically the province of Ontario, implications of supporting education for all through the framework of inclusive education are examined. These implications include funding, teaching commitment and training, resources, and privatization. Inclusive education refers to the ability of all students, regardless of gender, socioeconomic background, sexual orientation, or ability, to attend their neighborhood community school and be in classes with similar aged peers. Students with special education needs, whether these be learning disabilities, visual or hearing disorders, or mental health disorders, among many other conditions, are key stakeholders in inclusive education. The conclusion raises important questions for future research to examine inclusive education and the parallel implications not only in economically wealthy countries but for all jurisdictions that are trying to initiate and support educational programs for all students.

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)0.002
metaresearch head score (Gemma)0.005
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.381
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.182
GPT teacher head0.478
Teacher spread0.296 · 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
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

Citations2
Published2020
Admission routes1
Has abstractyes

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