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Record W2092680058 · doi:10.1080/01459350903107418

Professional Issues of Child and Youth Care Through the Language Lens

2008· article· en· W2092680058 on OpenAlexaff
Kiaras Gharabaghi

Bibliographic record

VenueChild & Youth Services · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicImpact of Education Environments
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsJargonVariety (cybernetics)Perspective (graphical)PedagogyYouth workWork (physics)Child careSociologyPsychologyNursingMedical educationPublic relationsMedicineLinguisticsPolitical scienceComputer science

Abstract

fetched live from OpenAlex

SUMMARY This article explores the role of language and forms of communication in professional child and youth care practice. It is argued that all the professional issues of child and youth care practice are significantly impacted by language and the manner in which practitioners use language and a variety of communication forms to articulate their work. The role of jargon in child and youth care practice is examined using several commonly used terms as examples. The need for an ongoing, critical perspective in the use of language is emphasized, and practitioners are encouraged to contemplate the biases and unexamined truths embedded in their day-to-day language use.

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)0.006
metaresearch head score (Gemma)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.025
Scholarly communication0.0110.004
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.020
GPT teacher head0.303
Teacher spread0.283 · 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

Citations1
Published2008
Admission routes1
Has abstractyes

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