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Record W2154661439 · doi:10.22230/ijepl.2010v5n12a232

TEACHERS’ PASTORAL ROLE IN RESPONSE TO THE NEEDS OF ORPHANED LEARNERS

2011· article· en· W2154661439 on OpenAlexvenueno aff
Teresa Auma Ogina

Bibliographic record

VenueInternational Journal of Education Policy and Leadership · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Education Studies and Reforms
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyPastoral carePedagogySchool teachersMathematics educationMedical educationMedicineNursing

Abstract

fetched live from OpenAlex

This article discusses a study that explored the way teachers perceive and describe their roles in responding to the needs of orphaned learners. The participants in the study were three secondary and two primary school teachers. The data on the teachers’ experiences were collected through semi-structured interviews. The findings revealed that, although some of the teachers struggle to fulfil some of the orphaned learners’ needs, most were unable to cope with the roles of teaching and learning and care giving. The study identifies a lack of skills for supporting grieving learners and the resources needed to do so effectively. The implications of the findings are that there is a need for teacher development in terms of equipping teachers with the knowledge and skills required for pastoral care. It may also be prudent for the state to consider appointing counsellors and social workers at schools to assist teachers and orphaned learners.

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)0.004
metaresearch head score (Gemma)0.010
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 score0.008
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0080.007
Scholarly communication0.0040.003
Open science0.0010.005
Research integrity0.0010.003
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 head0.150
GPT teacher head0.380
Teacher spread0.230 · 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

Citations15
Published2011
Admission routes1
Has abstractyes

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