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Record W2115663640 · doi:10.1177/0143034313508875

Children’s rights and school psychology: Historical perspective and implications for the profession

2014· article· en· W2115663640 on OpenAlexaff
Stuart N. Hart, Brannon W. Hart

Bibliographic record

VenueSchool Psychology International · 2014
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsInternational Institute for Child Rights and Development
Fundersnot available
KeywordsSchool psychologyChampionConvention on the Rights of the ChildPromotion (chess)Psychological interventionPerspective (graphical)PedagogyPsychologyPolitical scienceHuman rightsSociologyLawPolitics

Abstract

fetched live from OpenAlex

School psychology and children’s rights have great potential, well beyond what has been realized, for advancing the best interests of children, their communities, and societies. A child rights approach infused into school psychology can significantly contribute to the fulfillment of this potential. To respect and illuminate these factors and possibilities, a brief history of children’s rights is presented, its major components as embodied in the UN Convention on the Rights of the Child and their relevance for education and the school community are clarified, and the opportunities for school psychology to champion and deeply integrate children’s rights in policy and practice are explored. Employing this base, a proposal is made for a new social contract between school psychology and those it serves which moves beyond reactive problem oriented interventions to give primacy to proactive promotion of the well-being and full holistic development of the child, employing a prospective human development models emphasizing progressive achievement of self-stewardship for all children.

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)0.004
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 score0.012
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0090.042
Scholarly communication0.0090.009
Open science0.0010.005
Research integrity0.0050.010
Insufficient payload (model declined to judge)0.0050.000

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 head0.022
GPT teacher head0.365
Teacher spread0.342 · 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

Citations40
Published2014
Admission routes1
Has abstractyes

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