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Managing Flexibility Without Security in Toronto’s Direct Funding

2020· book-chapter· en· W4205752338 on OpenAlexaboutno aff
Cynthia J. Cranford

Bibliographic record

VenueCornell University Press eBooks · 2020
Typebook-chapter
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsnot available
Fundersnot available
KeywordsFlexibility (engineering)NegotiationEarningsSplit labor market theoryContext (archaeology)Labour economicsPosition (finance)BusinessWork (physics)Labor relationsSecondary labor marketPolitical scienceEconomicsFinanceManagement

Abstract

fetched live from OpenAlex

This chapter examines the Direct Funding Program of Ontario's Self-Managed Attendant Services. The evident willingness of self-managers and personal attendants to engage in relational work and the still unmet labor market security of workers were both necessary for self-managers to realize the Direct Funding Program's promise of flexibility. However, within a context of insufficient funding and little to no collective backing, this program produced labor market insecurity for workers, in the form of insufficient hours, earnings, and protection. Moreover, the position of workers in the broader racialized and gendered labor market shaped their labor market choices, or lack thereof, and shaped their experience at the intimate level. Failing to address broader racialized and gendered labor market insecurity not only has implications for workers who are less able to negotiate what they do and how. It also limits the progressive potential to value all forms of intimate labor and to rethink skill.

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)0.001
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: none
Teacher disagreement score0.186
Threshold uncertainty score0.474

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0070.006
Scholarly communication0.0070.002
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.001

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 head0.116
GPT teacher head0.330
Teacher spread0.214 · 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
Published2020
Admission routes1
Has abstractyes

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Same venueCornell University Press eBooksSame topicEmployment and Welfare StudiesFrench-language works237,207