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Record W3130880864 · doi:10.1093/bjsw/bcab011

Today in Light of Yesterday: An Exploration of Workers’ Childhood Memories in the Context of Child Protection Practice

2021· article· en· W3130880864 on OpenAlexaff
Sean A R St. Jean, Brian Rasmussen, Judy Gillespie, Daniel Salhani

Bibliographic record

VenueThe British Journal of Social Work · 2021
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsChild protectionNarrativeYesterdaySocial workContext (archaeology)PsychologyInterpretative phenomenological analysisDevelopmental psychologyNarrative inquiryEarly childhoodSocial psychologyQualitative researchMedicineSociologyNursingPolitical scienceSocial science

Abstract

fetched live from OpenAlex

Abstract Child protection workers are routinely faced with emotionally intense work, both personally and vicariously through the traumatic narratives and experiences of parents and children. What remains largely unknown is how child protection workers’ own childhood memories might influence the manner in which they experience and are affected by those narratives. The aim of this explorative study was to use Interpretive Phenomenological Analysis as a research methodology to answer the research question, ‘In what ways do social workers experience, and make sense of, their own childhood memories in the context of their child protection practice?’ Semi-structured interviews were conducted with eight child protection workers, aiming to understand their personal and professional experiences with regard to this question. The study found a relationship between various forms of childhood adversity and the presence of negative present-day triggers when participants were faced with practice scenarios that bore similarity to those experiences. Implications with regard to child protection worker well-being, countertransference and risk decision-making 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 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.728
Threshold uncertainty score0.256

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.029
GPT teacher head0.296
Teacher spread0.267 · 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

Citations3
Published2021
Admission routes1
Has abstractyes

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