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Record W3212174972 · doi:10.32920/ryerson.14648340.v1

How do they do it? : perspectives on being an educational assistant in an Ontario classroom

2021· preprint· en· W3212174972 on OpenAlexaffabout
Patricia Marie Hodgson

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicCollaborative Teaching and Inclusion
Canadian institutionsToronto Metropolitan UniversityEducation and Early Childhood Development
Fundersnot available
KeywordsSituatedGrounded theoryPedagogyQualitative researchPsychologyParticipant observationSociologyComputer scienceSocial science

Abstract

fetched live from OpenAlex

This qualitative study examined the roles and responsibilities of educational assistants from their own perspectives. Five educational assistants kept written journals and each participant was interviewed once. Findings were interpreted through a critical lens which allowed an examination of the relationships within the hierarchical power structure of the school system and where the educational assistants were situated. A grounded theory approach explained the factors which influenced the perspectives of the participants on being an educational assistant in an Ontario classroom. These factors were identified and organized in five major categories: 1) roles and responsibilities, 2) relationships, 3) communication, 4) changes, and 5) training. The interrelationships between these categories highlighted the complex nature of the role of the educational assistant. This study concluded that relationships and communication had a major influence on the perspectives of the educational assistants.

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)0.011
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.280
Threshold uncertainty score0.564

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0210.015
Scholarly communication0.0060.003
Open science0.0020.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.034
GPT teacher head0.351
Teacher spread0.317 · 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 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
Published2021
Admission routes2
Has abstractyes

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