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Record W3043555660

Compassion fatigue in child protection workers in Northeastern Ontario

2019· dissertation· en· W3043555660 on OpenAlexaboutno aff
Melissa Raymond

Bibliographic record

VenueLu Zone Ul (Laurentian University) · 2019
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Farm Safety
Canadian institutionsnot available
Fundersnot available
KeywordsCompassion fatigueChild protectionCompassionPsychologyClinical psychologyMedicineNursingPolitical scienceBurnoutLaw
DOInot available

Abstract

fetched live from OpenAlex

A career in the child protection sector is one of the most complex roles in the social work profession. Child protection worker (CPW) duties include accepting referrals, conducting investigations of allegations or evidence that children are experiencing abuse, and protecting children from abuse where necessary. This can include providing short- or long-term intervention with families, or ultimately removing children from their homes, where the risks are too great to be mitigated with less intrusive measures. CPWs are on-call and available 24-hours per day, 7-days per week. Due to the demanding nature of the career, CPWs often experience symptoms of compassion fatigue which can manifest in many symptoms, such as physical, emotional, and mental distress and disturbances. The aim of this qualitative research thesis was to examine the experiences of CPWs in Northeastern Ontario through individual interviews with CPW retirees. A total of 11 retirees were individually interviewed. The interviews were then transcribed and qualitatively analyzed using a thematic analysis approach. Three main themes were constructed from the responses: Quality/Impact of the Work; Recruitment and Retention; and Recommendations for Improvement. This thesis describes four implications of this study: the impact on CPWs’ well-being; the importance of increased training; the necessity of clinical supervision and debriefing; as well as the significance of peer-to-peer learning. Lastly, study limitations, as well as considerations for future research, are discussed.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.064
Threshold uncertainty score0.345

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0140.006
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.012
GPT teacher head0.183
Teacher spread0.171 · 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
Published2019
Admission routes1
Has abstractyes

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