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Record W4243820612 · doi:10.32920/ryerson.14640315

Benefits and Challenges to People with Psychiatric Disabilities Who Volunteer

2021· preprint· en· W4243820612 on OpenAlexaff
Agnes Meinhard, Itay Greenspan, Jennifer Paterson, Phaedra Livingstone

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsToronto Metropolitan UniversityVictoria ParkYork University
Fundersnot available
KeywordsCitationPsychologyLearning disabilityPsychiatryMedical educationMedicineLibrary scienceComputer science

Abstract

fetched live from OpenAlex

This research follows from the research reported in CVSS Working Paper Series, Volume 2007 (2). In that paper we presented the results of our examination of volunteer programs in ten organizations serving people with psychiatric disabilities2. We described the nature of the programs, identified best practices and discussed the challenges and benefits they presented. This paper focuses on the responses of 27 people with psychiatric disabilities to a questionnaire probing their volunteering experiences. Please refer to the previous CVSS Working Paper titled “Client Volunteering in Organizations Serving Individuals with Psychiatric Disabilities” for a detailed review of the literature. Here we will briefly summarize the major thrust of the literature review. Keywords: CVSS, Centre for Voluntary Sector Studies, Working Paper Series, TRSM, Ted Rogers School of Management Citation:

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)0.010
metaresearch head score (Gemma)0.031
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 score0.010
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.031
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0100.005
Scholarly communication0.0050.003
Open science0.0010.009
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.102
GPT teacher head0.381
Teacher spread0.279 · 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
Published2021
Admission routes1
Has abstractyes

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