MétaCan
Menu
Back to cohort
Record W2901733134

Different Numbers, Different Stories: Problematizing "Gaps" in Ontario and the TDSB

2018· article· en· W2901733134 on OpenAlexaffvenueabout
Vidya Shah

Bibliographic record

VenueCanadian Journal of Educational Administration and Policy · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsYork UniversityUniversity of Toronto
Fundersnot available
KeywordsTransformative learningSociologyFocus groupEducational equityEquity (law)Critical discourse analysisDiscourse analysisDisadvantagedPedagogyGender studiesPublic relationsPolitical sciencePoliticsLaw
DOInot available

Abstract

fetched live from OpenAlex

As an urban district reform for equity, the Model Schools for Inner Cities (MSIC) Program in the Toronto District School Board (TDSB) was founded as a response to inequities in the city and opportunity gaps among groups of students. This study critically explores the equity discourses among various stakeholders in the MSIC Program between 2004-14, with a specific focus on how opportunity gaps are conceptualized. Critical discourse analysis was used with attention to how these discourses interacted within and between two sets of sixteen participant interviews and the analysis of twelve documents, as well as how the discourses changed over time. A spectrum of thinking emerged from the data on opportunity gap discourses, with Affirmative Discourses on the one hand, and transformative discourses on the other and included four components. Three of the four components were adapted from the work of Fraser’s (2005) tripartite theory of justice (Redistribution, Recognition and Representation). The fourth component emerged from the data and will be referred to as Re-education.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.736
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.077
GPT teacher head0.374
Teacher spread0.297 · 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 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

Citations13
Published2018
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Educational Administration and PolicySame topicTeacher Education and Leadership StudiesFrench-language works237,207