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Record W2157037176

Regulated Out of Existence: A Case Study of Ottawa's Ticket Defence Program

2014· article· en· W2157037176 on OpenAlexaffabout
Suzanne Bouclin

Bibliographic record

VenueSSRN Electronic Journal · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Law and Evidence
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsTicketLicenseAccountabilityContext (archaeology)Political scienceLegislatureScope (computer science)Work (physics)Public administrationService (business)BusinessPublic relationsLawEngineeringGeographyComputer security
DOInot available

Abstract

fetched live from OpenAlex

The centrepiece of this research is a case study of the Ticket Defence Program (TDP). Between 2003 and 2007, the TDP, an Ottawa-based collective of volunteers, provided vital and effective legal assistance to street-involved people charged with minor provincial or municipal offences. While some of the TDP’s work resembled the work of a paralegal (such as requesting disclosure and appearing in provincial court), none of its members were licensed to provide legal services in Ontario. In the first part of this article, I provide the historical and legislative context to paralegal regulation in Ontario that informed the Paralegal Standing Committee’s (Paralegal Committee) interactions with the TDP. In the second part, I survey the TDP’s structure, accountability mechanisms, and operations developed to address the unmet legal needs of Ottawa’s street-involved people. In the third part of this article, I examine the Paralegal Committee’s decision, on the one hand, not to recognize the TDP as a group beyond the scope of the Law Society Act (which would not require a paralegal license to provide its service) and, on the other, not to exempt the TDP from the new regulatory structure (requiring the TDP to obtain a license in order to continue to provide legal services).

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.674
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.031
GPT teacher head0.352
Teacher spread0.321 · 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 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
Published2014
Admission routes2
Has abstractyes

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Same venueSSRN Electronic JournalSame topicCriminal Law and EvidenceFrench-language works237,207