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Record W1863198108

Enhancing Understanding of the Nature of Supportive School-based Relationships for Youth who have Experienced Trauma

2013· article· en· W1863198108 on OpenAlexaffvenue
Jennifer Dods

Bibliographic record

VenueCanadian Journal of Education / Revue canadienne de l éducation · 2013
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsQueen's University
Fundersnot available
KeywordsAttunementMental healthPsychologySocial connectednessContext (archaeology)PedagogyMedical educationSocial psychologyPsychotherapistMedicine
DOInot available

Abstract

fetched live from OpenAlex

Student-teacher relationships play a critical role in supporting the learning and well-being of students with mental health problems. The purpose of this article was to draw from both current literature and previous qualitative interview research to understand the aspects of school-based relationships that are beneficial for students who have experienced trauma. The integration of theory with the first-person accounts of the youth led to the development of a model that describes the core needs created by experiencing trauma and the nature of student-teacher relationships that can meet these needs in the educational context.  The four aspects of student teacher relationships that supported trauma-related needs at school were relationships that were 1) teacher driven, 2) authentic caring, 3) attunement to students’ emotional states, and 4) individualized. Establishing caring connections with teachers was pivotal to student health and well-being and to meeting the core needs created by traumatic events (safety, control, trust, self-worth, self-expression, connections).  As youth with mental health problems spend considerable time each week in the classroom, a greater understanding of the nature of supportive school-based relationships can inform teachers in their efforts to teach and connect with students. Keywords: mental health, trauma, student-teacher relationships, school connectedness

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.458
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.076
GPT teacher head0.299
Teacher spread0.223 · 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

Citations45
Published2013
Admission routes2
Has abstractyes

Explore more

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