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Aligning Perspectives of Subjective Well-Being: Comparing Spouse and Colleague Perceptions of Social Worker Happiness

2014· article· en· W14019307 on OpenAlexaff
John R. Graham, Micheal L. Shier, Andrea Margaret Newberry, Elena Esina

Bibliographic record

VenueThe Qualitative Report · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPsychologySocial workWell-beingSocial psychologyHappinessBurnoutSpouseQualitative researchPerspective (graphical)SociologyClinical psychology

Abstract

fetched live from OpenAlex

Social workers experience higher rates of burnout and attrition when compared to other health related occupational groups. Previous research on the well being of social workers has tended to focus on the social workers themselves. But the development of well-being is dynamic and is fostered through relationships and interactions with others. In the case of social workers, these relationships include workplace, professional, and personal life interactions. This research sought to better understand the level of congruence between a social worker’s perspective of well-being and perspectives held by significant people in their workplace and at home. Utilizing qualitative methods we interviewed colleagues and spouses (n=10) of social workers that were found to have high levels of work-related subjective well-being. The findings support previous conclusions on the positive subjective well-being (SWB) of practicing social workers, but also indicate a lack of a deeper understanding of the nuances that contribute to social worker SWB. These findings are particularly useful for social workers trying to enhance their SWB, and have direct applicability in education and professional development settings that seek to enhance social worker self-care.

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)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.261
Threshold uncertainty score0.839

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.078
GPT teacher head0.477
Teacher spread0.400 · 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.

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

Citations9
Published2014
Admission routes1
Has abstractyes

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