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Record W2606687708 · doi:10.14507/epaa.25.2716

Market “choices” or structured pathways? How specialized arts education contributes to the reproduction of inequality

2017· article· en· W2606687708 on OpenAlexaffabout
Rubén Gaztambide‐Fernández, Gillian Parekh

Bibliographic record

VenueEducation Policy Analysis Archives · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicUrban, Neighborhood, and Segregation Studies
Canadian institutionsUniversity of TorontoInstitute for Christian Studies
FundersOffice of International Science and Engineering
KeywordsThe artsPopulationCultural capitalInequalitySociologyReputationPublic relationsPsychologyMathematics educationPolitical scienceSocial scienceDemography

Abstract

fetched live from OpenAlex

Located in one of the most diverse cities in the world, the Toronto District School Board (TDSB) offers several programs catering to a variety of student interests. Specialty Arts Programs (SAPs) have gained particular attention in part because of their reputation as excellent schools providing a unique opportunity for training in the arts. However, recently such programs have also raised concerns about who can access and who ultimately benefits from specialized programming in the arts. While the TDSB is committed to equal access for all families, the student populations at these programs do not mirror the broader school population, serving mostly affluent families and students with access to high levels of social and cultural capital. Employing data from the TDSB’s Parent and Student Census and the School Information Systems, the article first demonstrates the demographic homogeneity of specialized arts programs and then examines whether this homogeneity is a particular outcome of specialized arts programs or a manifestation of a de facto streaming mechanism that begins earlier in the schooling process. To do this, the authors explore the relationship between feeder schools and programs that guide students towards SAPs. Results demonstrate that the bulk of SAP students are drawn from a select few elementary schools across the board. Largely, the demographics of elementary feeder schools reflect similar characteristics of the SAP population and this relationship is amplified as the number of students drawn from feeder schools increases. In addition, students in SAPs experience a high level of belonging in school as compared to students across the system. While this outcome is often attributed to the immersion in arts-based curriculum, the authors query how the role of creating homogenous spaces through selective programming contributes to students’ experience of belonging while at the same time reproducing structural inequality.

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)0.003
metaresearch head score (Gemma)0.013
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.118

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0020.010
Scholarly communication0.0070.009
Open science0.0010.006
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0350.001

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 head0.063
GPT teacher head0.387
Teacher spread0.324 · 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

Citations62
Published2017
Admission routes2
Has abstractyes

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