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Record W3117915439 · doi:10.18357/ijcyfs114.2202019991

SYSTEMIC REFLEXIVITY IN RESIDENTIAL CHILD CARE: A PEDAGOGICAL FRAME TO EMPOWER PROFESSIONAL COMPETENCE

2020· article· en· W3117915439 on OpenAlexvenueno aff
Laura Formenti, Allessandra Rigamonti

Bibliographic record

VenueInternational Journal of Child Youth and Family Studies · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsnot available
Fundersnot available
KeywordsReflexivityTransformative learningCompetence (human resources)PedagogyNarrativePsychologySocial workSociologyKnowledge managementComputer scienceSocial psychologyPolitical science

Abstract

fetched live from OpenAlex

This position paper offers a pedagogical frame to empower professional work in residential child care. Jobs in this demanding field are characterized by daily relationships with children of different ages, needs, and cultural backgrounds. There is a need for effective communication and interaction with them, their families, co-workers, other professionals, and care agencies, as well as with the larger community. This complexity brings uncertainty and the necessity of thinking and acting in a sensitive way in order to open possibilities for systemic transformation at the micro, meso, and macro levels. In this framework, we focus on reflexivity as a meta-competence — a set of specific postures, competences, and attitudes that characterize expert professional action. A thorough literature review on reflexivity in social work and child protection is aimed at clarifying the meanings, uses, and features of this concept. We claim that systemic reflexivity can be used as a framework, a methodology, and a set of tools to empower professional work by enhancing emotional, cognitive, and epistemic self-awareness, systemic wisdom, abduction, and active listening. To help workers and teams develop these five competences, a self-directed learning module is currently being designed, based on systemic and narrative perspectives, and transformative learning theory.

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)0.002
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 score0.251
Threshold uncertainty score0.343

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.134
GPT teacher head0.463
Teacher spread0.329 · 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
Published2020
Admission routes1
Has abstractyes

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