MétaCan
Menu
Back to cohort

Hospital Volunteers and Carework*

2007· article· fr· W2101222371 on OpenAlexaffabout
Muriel Mellow

Bibliographic record

VenueCanadian Review of Sociology/Revue canadienne de sociologie · 2007
Typearticle
Languagefr
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsLimitingPsychologyWork shiftDemographyHumanitiesSociologyGerontologyMedicineArt

Abstract

fetched live from OpenAlex

L'auteure analyse les soins fournis par des bénévoles d'hôpitaux en utilisant des données d'entrevues, des descriptions de täches et des statistiques concernant les bénévoles de quatre hôpitaux d'Alberta, Canada. Les employés des hôpitaux s'attendent à ce que les bénévoles fournissent des soins instrumentaux et affectifs, mais ils restreignent également leur tàche en imposant des limites aux heures de travail réalisé par les bénévoles ainsi qu'à la somme d'information qu'ils reçoivent sur les patients. Les bénévoles surmontent ces contraintes en entretenant des conversations informelles destinées à augmenter leurs connaissances, tout en étant flexibles par rapport aux heures accordées aux patients, afin de pouvoir s'occuper de leurs besoins émotionnels. L'auteure considère également la répartition des sexes chez les bénévoles et l'influence qu'elle exerce sur leurs attentes. Carework done by hospital volunteers is examined using interview data, task descriptions and volunteer statistics from four hospitals in Alberta, Canada. Hospitals expect volunteers to provide instrumental and affective care but also constrain this work by limiting volunteers' work time and the amount of information they are given about patients. Volunteers overcome these constraints by initiating informal conversation to broaden their knowledge and capitalizing on flexibility in how they spend their time to attend to patients' emotional needs. I also consider how the volunteer workforce is gendered and how this influences expectations of volunteers.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.429
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.006
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.031
GPT teacher head0.289
Teacher spread0.258 · 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 teacher head, not a consensus.

Study designObservational
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
Published2007
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Review of Sociology/Revue canadienne de sociologieSame topicNonprofit Sector and VolunteeringFrench-language works237,207