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Record W4382582549 · doi:10.15270/59-2-1121

“MUCH OF OUR COUNSELLING IS ABOUT YOUR FACIAL EXPRESSION AND AUTHENTICITY”: SCHOOL-BASED COUNSELLING DURING COVID-19 IN KWAZULU-NATAL PROVINCE

2023· article· en· W4382582549 on OpenAlexaff
Ajwang’ Warria, Kerry-Jane Coleman, Cyndirela Chadambuka

Bibliographic record

VenueSocial Work/Maatskaplike Werk · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicFamily Support in Illness
Canadian institutionsUniversity of TorontoUniversity of Calgary
Fundersnot available
KeywordsPsychosocialPsychological interventionPsychosocial supportTransformative learningNursingCoronavirus disease 2019 (COVID-19)Intervention (counseling)MedicineInterpersonal communicationPsychologyMedical educationPedagogyPsychotherapistSocial psychology

Abstract

fetched live from OpenAlex

Maintaining therapeutic care of learners during and after COVID-19 in South Africa has required significant changes to the way that counselling is provided in schools. While some of these changes are well documented, there are critical gaps regarding the experiences of school counsellors during the pandemic period, globally and in South Africa. Hence this qualitative study sought to explore the experiences of school psychosocial practitioners who are rendering supportive services in private schools in KwaZulu-Natal Province. While the findings show that remote/online therapy is a valid option, all schools should ensure that therapists have adequate resources and the necessary collaboration to provide effective services to the school community. Furthermore, interpersonal, organisational, practice, policy and advocacy-oriented adaptations are required in establishing transformative interventions in all schools to address trauma. Keywords: counselling, COVID-19, psychosocial intervention, schools, South Africa

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.278
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.042
GPT teacher head0.335
Teacher spread0.293 · 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.

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
Published2023
Admission routes1
Has abstractyes

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