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“Suffering in silence”: How social workers in child welfare practice experience and manage burnout

2024· article· en· W4402830373 on OpenAlexaffabout
Sulemana Fuseini

Bibliographic record

VenueChildren and Youth Services Review · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsLambton College
Fundersnot available
KeywordsBurnoutSilenceWelfareSocial workSocial WelfarePsychologyNursingMedicineClinical psychologyPolitical scienceEconomic growthEconomics

Abstract

fetched live from OpenAlex

Social workers in child welfare practice encounter dilemmas, tensions, contradictions, ambiguities, and ambivalence as they attempt to meet the competing demands of the Tri-sphere — the formal child welfare system, the professional theories and values guiding practice, and the child welfare service recipients. This study explored how these encounters result in worker burnout and how that is managed. The study used a constructivist grounded theory approach. Data were collected in St. John’s, NL, Canada, employing in-depth individual interviews with 18 frontline child welfare social workers. Findings reveal that child welfare social workers regularly experience varied feelings and emotions of burnout and utilize a variety of self-care strategies to manage. Recommendations include a call for child welfare agencies to provide opportunities for workers to feel heard and acknowledged about any negative feelings and emotions, strengthen positive peer supports, and promote essential self-care practices such as offering reduced membership cost for physical activities.

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)0.001
metaresearch head score (Gemma)0.000
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: none
Teacher disagreement score0.543
Threshold uncertainty score0.671

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.016
GPT teacher head0.336
Teacher spread0.320 · 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

Citations8
Published2024
Admission routes2
Has abstractyes

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