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Enregistrement W4389815149 · doi:10.18438/eblip30325

Experiences of Visible Minority Librarians and Students in Canada from the ViMLoC Mentorship Program

2023· article· en· W4389815149 sur OpenAlexaffvenueabout
Yanli Li, Valentina Ly, Xuemei Li

Notice bibliographique

RevueEvidence Based Library and Information Practice · 2023
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueLibrary Science and Information Literacy
Établissements canadiensYork UniversityUniversité du Québec à MontréalUniversité de MontréalUniversité LavalWilfrid Laurier UniversityUniversity of OttawaLibrary and Archives Canada
Organismes subventionnairesnon disponible
Mots-clésMentorshipHelpfulnessMedical educationPsychologySession (web analytics)MedicineSocial psychologyComputer science

Résumé

récupéré en direct d'OpenAlex

Objective – The purpose of this research is to examine the experiences of mentors and mentees in the formal mentorship program offered by the Visible Minority Librarians of Canada Network (ViMLoC) from 2018-2022. Findings from this research will help mentors and mentees understand how to establish an effective mentoring relationship. Professional library associations and libraries can also gain valuable insights to support the visible minority library professionals within their own mentorship programs. Methods – Between 2018 and 2022, 113 mentors and 145 mentees participated in four sessions of the ViMLoC mentorship program. The ViMLoC Mentorship Committee designed and delivered a survey for mentors and a survey for mentees at the end of each session. Over four sessions, 81 mentors and 82 mentees completed the surveys, representing a 72% and 57% completion rate, respectively. Fisher's Exact Tests were performed to examine if there were significant differences between mentors and mentees in their perceptions regarding ease of communication, relationship, helpfulness of mentorship, likeliness of keeping in contact, and importance of having a visible minority partner. Results – The mentees perceived mentoring support to be more helpful than the mentors perceived it themselves. The mentees were more likely to keep in contact with their mentors beyond the mentorship program while the mentors did not show as much interest. The mentees who had a positive experience from the formal mentorship program were found to be more likely to mentor others in the future, whereas the same effect did not hold true for the mentors. On the other hand, some findings were the same for both mentors and mentees. Both stated that effective communication would facilitate a good mentoring relationship, which in turn, would lead to positive outcomes and greater likelihood of keeping in contact beyond the mentoring program. There was also consensus of opinion about the most important areas of mentoring support and some essential skills for building a successful mentoring relationship. Conclusion – This research contributes to the literature by using an empirical research method and comparative analyses of the experiences between mentors and mentees over four sessions of the ViMLoC mentorship program. The study focuses on the perceptions of participants regarding their communication, relationship, helpfulness of mentorship, associations between their past and present mentoring experiences, areas of support, importance of having a visible minority partner, and essential skills for building a successful mentoring relationship. Mentors and mentees differed significantly in how they perceived the helpfulness of mentorship support and how likely they would like to maintain the ties beyond the program. For both sides, effective and easy communication was found to be critical for building a good mentoring relationship and achieving a satisfactory experience.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCommunication savante
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,533
Score d'incertitude au seuil0,880

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,416
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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 Opus0,020
Tête enseignante GPT0,302
Écart entre enseignants0,283 · 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 tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

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

En bref

Citations1
Publié2023
Routes d'admission3
Résumé présentoui

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