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Record W2338822298 · doi:10.1177/0020872816633889

Incorporating individual community assets in neighbourhood houses: Beyond the community-building tradition of settlement houses

2016· article· en· W2338822298 on OpenAlexafffundabout
Miu Chung Yan, Sean Lauer, Pilar Riaño‐Alcalá

Bibliographic record

VenueInternational Social Work · 2016
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsNeighbourhood (mathematics)Settlement (finance)Community buildingCommunity organizationEconomic growthSociologyBusinessPublic relationsPolitical scienceFinanceEconomics

Abstract

fetched live from OpenAlex

As a global movement, neighbourhood houses (NHs) are found in urban communities all over the world. Following the community-building tradition of early settlement houses, NHs have been actively nurturing and mobilizing community assets to serve the local community, but it is not known whether NHs have incorporated these assets in their infrastructure. This article reports the findings of a clearinghouse survey of 15 NHs in Metro Vancouver, Canada, which indicate that they nurtured community assets and incorporated them into their infrastructure as paid staff. Yet at the leadership level, the incorporation falls short of ethno-racial minority members from the community.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.042
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.008
Scholarly communication0.0050.003
Open science0.0010.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.100
GPT teacher head0.410
Teacher spread0.311 · 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

Citations7
Published2016
Admission routes3
Has abstractyes

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