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Record W4401407102 · doi:10.1093/socpro/spae042

Bridging Divides or Reinforcing Distance? The Interplay of Individual and Organizational Factors in Shaping Volunteers’ Relationships with Criminalized Women

2024· article· en· W4401407102 on OpenAlexaboutno aff
Kaitlyn Quinn

Bibliographic record

VenueSocial Problems · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsnot available
Fundersnot available
KeywordsTypologyEquity (law)InequalityReproductionSocial WelfareSociologyWelfarePublic relationsPolitical scienceLaw

Abstract

fetched live from OpenAlex

Abstract As governments cut funding for social welfare programs and shift toward neoliberal, marketized alternatives, non-profits have taken on a large and growing role in the provision of services to marginalized people. This paper examines how volunteers approach their relationships with service users in non-profits, as well as the consequences of and explanations for variation in their approaches. This research explores these questions ethnographically within Canadian non-profits offering social services to criminalized women. This paper offers three interrelated contributions. The first is a typology of different volunteer approaches within the penal voluntary sector—constructing volunteers as bystanders, tourists, visitors, or apprentices in their relationships with criminalized women. The second highlights how some of these approaches entrench social distance and inequality, whereas others encourage greater proximity and equity between volunteers and criminalized women. The third demonstrates how variation in volunteers’ approaches is the product of a dynamic interplay of individual and organizational factors. Together, these findings provide new insights about the conditions under which volunteers can do “good” or “bad” within non-profits. These insights could enhance the quality of volunteer work, reduce the reproduction of inequalities, and support the operation of organizations delivering vital services to marginalized people.

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)0.003
metaresearch head score (Gemma)0.009
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 score0.052
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.011
Scholarly communication0.0040.002
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.055
GPT teacher head0.307
Teacher spread0.252 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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