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Enregistrement W55299528

The Case for In-School Monitoring.

2003· article· en· W55299528 sur OpenAlexaboutno aff
Karen Hancock

Notice bibliographique

RevueEducation Canada · 2003
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueEarly Childhood Education and Development
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésCommitImprisonmentPsychologyDevelopmental psychologySocial psychologyCriminology
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Anecdotal reports and academic literature have documented the positive impact of a caring adult on a child’s life. Developmental psychologists generally agree that all children need an adult in their lives who is crazy about them. Resiliency research has found that children who were able to cope despite difficult circumstances identified a single factor as most helpful: one significant adult in their lives, who showed and maintained a real interest in and connection with them. In family circumstances where the child does not have that one consistent, interested adult – whether that is due to death, divorce, imprisonment, or parents working many jobs – the resiliency and outcomes are not as positive. But, mentors can fill the gap. Informal mentors are adults – such as sports coaches, teachers, relatives or neighbours – who already have a place in a child’s life. Big Brothers Big Sisters (BBBS) have formalized the mentor process to strategically provide mentors for children and youth who do not have such a significant, caring adult in their lives. In BBBS programs, mentors are adults who are unrelated to the child and who commit time to spend with the child each week, for at least a year. Independent research has demonstrated the positive impact of mentoring on the lives of children in areas such as academics, attitude, anti-social behaviour, decisionmaking, and relationships with peers, parents and other adults. The need for mentoring has never been so great. The Progress of Canada’s Children report states that the number of children under 12 years old whose parents were separated or divorced has tripled in the last 20 years; that children in sole-parent families are at greater risk of poor development than other children if the family is very poor or lives in an unsafe neighbourhood; and that the number of poor children grew from 1.36 million in 1995 to 1.5 million in 1996. Yet, for a variety of reasons (family responsibility, increased mobility, work commitments, etc.), the number of people who are willing or able to make the commitment to a community-based match is dropping. So, while we know that mentoring works, it has become more difficult to make the match that makes such a difference in a child’s life. In response to these two trends – increasing numbers of children who are in need coupled with a decreasing pool of volunteers – Big Brothers Big Sisters of Canada has launched a national In-School Mentoring program that allows local agencies to provide many more mentors to children. ISM is an activity-based program where the mentor and mentee meet on school property, during school hours, for one hour each week. Employers generally support the volunteer mentors in their volunteer work by releasing them from work for the volunteer time. Volunteer mentors are recruited, screened and trained by the agency; however, the children are selected by the teachers. Children who have low self-esteem, who may be at risk of dropping out of school, or who need extra attention may be identified as most likely to benefit from a one-to-one relationship. Often these children live in single-parent families and are highly transient, moving from home to home and school to school. Because children do better if they are matched at a younger age and when the match lasts for a longer period of time, some schools target children in grades 2 to 4. Typically, older children and youth tend to be more peer-focused and are somewhat reluctant to be involved in the ISM program; group mentoring programs seem to be more effective with that age group.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,007
score de la tête « metaresearch » (Gemma)0,021
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: aucune
Score de désaccord entre enseignants0,069
Score d'incertitude au seuil0,230

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0070,021
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0060,006
Communication savante0,0060,012
Science ouverte0,0030,011
Intégrité de la recherche0,0090,015
Charge utile insuffisante (le modèle a refusé de juger)0,0690,012

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,016
Tête enseignante GPT0,308
Écart entre enseignants0,292 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations8
Publié2003
Routes d'admission1
Résumé présentoui

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