Changes in the Library Landscape Regarding Visible Minority Librarians in Canada
Notice bibliographique
Résumé
Objective – As a follow-up to the first 2013 survey, the Visible Minority Librarians of Canada (ViMLoC) network conducted its second comprehensive survey in 2021. The 2021 survey gathered detailed information about the demography, education, and employment of visible minority librarians (VMLs) working in Canadian institutions. Data from the 2021 survey and the analysis presented in this paper help us better understand the current library landscape, presented alongside findings from the 2013 survey. The research results will be helpful for professional associations and library administrators to develop initiatives to support VMLs. Methods – Researchers created online survey questionnaires using Qualtrics XM in English and translated them into French. We distributed the survey invitation through relevant library association electronic mail lists and posted on ViMLoC’s website, social networking platforms, and through their electronic mail list. The survey asked if the participant was a visible minority librarian. If the response was “No,” the survey closed. Respondents indicating "Yes" were asked 36 personal and professional questions of three types: multiple-choice, yes/no, and open-ended questions. Results – One hundred and sixty-two VMLs completed the 2021 survey. Chinese remained the largest ethnic identity, but their proportion in the survey decreased from 36% in 2013 to 24% in 2021. 65% were aged between 26 and 45 years old. More than half received their library degree during the 2010s. 89% completed their library degree in Canada, a 5% increase from 2013. The majority of librarians had graduated from University of Toronto (25%), followed closely by University of British Columbia (23%), and Western University (22%). Only 3% received their library degree from a library school outside North America. 34% of librarians earned a second master’s degree and 5% had a PhD. 60% of librarians had less than 11 years of experience. Nearly half worked in academic libraries. Most were located in Ontario and British Columbia. 69% of librarians were in non-management positions with 5% being senior administrators. 25% reported a salary above $100,000. In terms of job categories, the largest group worked in Reference/Information Services (45%), followed by Instruction Services (32%), and as Liaison Librarians (31%). Those working in Acquisitions/Collection Development saw the biggest jump from 1% in 2013 to 28% in 2021. 58% of librarians sought mentoring support, of whom 54% participated in formal mentorship programs, and 48% had a visible minority mentor. Conclusion – 35% more VMLs responded to the 2021 survey compared to the 2013 survey. Changes occurred in ethnic identity, generation, where VMLs earned a Master of Library and Information Science (MLIS) or equivalent degree, library type, geographic location, and job responsibilities. The 2021 survey also explored other aspects of the VMLs not covered in the 2013 survey, such as librarian experience, salary, management positions, and mentorship experience. The findings suggested that the professional associations and library administrators would need collaborative efforts to support VMLs.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,004 | 0,012 |
| Études des sciences et des technologies | 0,016 | 0,005 |
| Communication savante | 0,008 | 0,003 |
| Science ouverte | 0,002 | 0,005 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».