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Record W1967310784 · doi:10.1080/01900692.2014.903273

Assessing Performance in Shelters for Abused Women: Can “Caring Citizenship” Be Measured in “Value for Money” Accountability Regimes?

2014· article· en· W1967310784 on OpenAlexaffabout
Roma Harris, C. Nadine Wathen, Roxanna Lynch

Bibliographic record

VenueInternational Journal of Public Administration · 2014
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsWestern University
Fundersnot available
KeywordsAccountabilityCitizenshipValue (mathematics)Value for moneyPsychologyBusinessEconomicsSocial psychologyPolitical sciencePublic economicsLawStatisticsPolitics

Abstract

fetched live from OpenAlex

Results are reported from a study of shelters for abused women in Ontario, Canada, suggesting that what clients, managers, and frontline workers value most in shelter services is based on a care perspective in which ongoing relational support is seen as essential to effective service delivery. Presently, government-required metrics used to assess shelter services not only reflect a narrow, justice perspective where “fairness” is defined as equal access to publicly supported services, but reveal a New Public Management emphasis on efficiency in which the focus is more on the “what” than the “how” of practice. Findings are discussed in terms of their implications for the design of accountability systems for evaluating government-contracted social 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 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)0.019
metaresearch head score (Gemma)0.076
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 score0.213
Threshold uncertainty score0.423

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.076
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.008
Scholarly communication0.0030.003
Open science0.0020.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.128
GPT teacher head0.448
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 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

Citations15
Published2014
Admission routes2
Has abstractyes

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