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Record W2058566950 · doi:10.5539/gjhs.v2n2p172

The Status of a Trainee Teacher with Mental Health Problems: Dilemmas on Inclusion and Exclusion in Higher Education

2010· article· en· W2058566950 on OpenAlexvenueno aff
Lawrence Mundia

Bibliographic record

VenueGlobal Journal of Health Science · 2010
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare professionals’ stress and burnout
Canadian institutionsnot available
Fundersnot available
KeywordsInclusion (mineral)Mental healthInclusion–exclusion principleInclusion and exclusion criteriaPsychologyMedicineSocial psychologyPsychiatryPolitical scienceAlternative medicine

Abstract

fetched live from OpenAlex

The case study reports on a 22-year old female pre-service student teacher pseudo-named P who dropped out of her training programme in Brunei due to psychological problems. Brunei education system has both local and foreign students. For ethical reasons the nationality, ethnicity, and other identifying information of the student are withheld throughout this study. An informal interview and the MMPI-2 evaluation confirmed that P had many severe mental health problems that required a wide range of therapeutic interventions to address. Overall, the present study illustrated how gender, interpersonal relationships, and culture interacted to cause distress for P. In addition the results demonstrated the plight of a tertiary student with mental health problems in a developing country who seemed to be accorded low priority in comparison to peers with other severe disabilities. Moreover, the study also highlighted the importance of psychological assessment in educational counseling and the lack of adequate psychotherapy resources for students with high support needs in mental health. Unless appropriate intervention measures are instituted, the wastage rate among vulnerable students with challenging behaviors might increase in Brunei. Keywords:Psychological; assessment; mental; health; counseling; psychotherapy; education.

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)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.466
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
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 head0.050
GPT teacher head0.436
Teacher spread0.386 · 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 designObservational
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

Citations18
Published2010
Admission routes1
Has abstractyes

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