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Record W7132863133

The Politics of "Access": Undocumented Students and Enrollment in Toronto Schools

2014· dissertation· W7132863133 on OpenAlexaboutno aff
Francisco Javier Villegas

Bibliographic record

VenueTSpace · 2014
Typedissertation
Language
FieldSocial Sciences
TopicEducation and experiences of immigrants and refugees
Canadian institutionsnot available
Fundersnot available
KeywordsGrassrootsPoliticsImmigrationHegemonyWork (physics)Order (exchange)Resistance (ecology)Government (linguistics)
DOInot available

Abstract

fetched live from OpenAlex

Bordering occurs beyond ports of entry. It operates in spaces where immigration status is examined in order to participate or access a public good. In Ontario, schools serve as borders and often exclude undocumented migrant on the basis of status. At the same time, community activists work to erode border-zones and redefine "membership." This project tracks and analyzes one such initiative. It historicizes constructions of membership in relation to the Toronto District School Board and its "Students Without Legal Immigration Status Policy." This policy, discursively known as a "Don't Ask, Don't Tell" (DADT) policy stipulates that the Board would protect students by barring employees from asking, reporting, or sharing information regarding a family's immigration-status. However, the policy remains to be fully implemented, the Board has constructed procedures that make enrolment more difficult, and undocumented students continue to experience exclusion. . Thus, this project addresses the gaps in implementation as well as differing understandings of what constitutes "access."The project combines Anti-racist theory, LatCrit, border rhetoricity, and concepts developed by Frantz Fanon, and Antonio Gramsci. This framework facilitates the examination of the construction of internal borders along hegemonic understandings of membership, how these processes are facilitated by the dehumanization of undocumented migrants, and the resistance practices of migrants and their allies. Data stems from interviews, experiential knowledge, and grey literature. Interviews were conducted with fourteen differently located social actors including TDSB administrators and grassroots organizers. Grey literature from the TDSB, the Don't Ask, Don't Tell Coalition, and No One Is Illegal- Toronto was also examinedKey findings include the ways bureaucratic processes at the TDSB invisibilize undocumented migrants and the resultant hegemonic reproduction of bordering in spite of "access" policies. Additionally, this project highlights the strategies employed by community organizers to make Toronto a space of "non-compliance" to immigration authorities and how access to schooling is framed as a key component. Finally, different framings of "access" are examined. While Board practices equated access to the ability to enroll, local activists demanded broader understandings of this concept including recognition of the ways interrelated factors, including safety and access to other services affected schooling.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.137
Threshold uncertainty score0.992

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0260.021
Scholarly communication0.0090.002
Open science0.0010.008
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0080.000

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 head0.460
Teacher spread0.443 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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