Documents found
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102221.More information
Keywords: inclusion scolaire, élèves issu·e·s de l’immigration récente, diversité culturelle et linguistique du français, socioconstructivisme
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102222.
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102227.More information
Keywords: Chasse, Ruralité, Études de genre, Masculinisme, Condition féminine
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102228.More information
Keywords: Récit de chasse, littérature québécoise, Introduction
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102229.More information
The use of artificial intelligence (AI) systems in personnel recruiting and selection practices is proving to be an innovative way to promote the inclusive hiring of diversified personnel. AI would allow organizations to free themselves of certain subconscious biases that are likely to affect the staffing process, since it is based on objective decision-making. This article focuses on the perception of human resources management professionals (HRMPs) regarding the use of AI systems and inclusive personnel hiring practices, taking into consideration managing equity, diversity and inclusion in workplaces. Drawing on qualitative data (17 participants in three focus groups), this article is based on research conducted among HRMPs in Quebec. The results show that several barriers to recruiting and selecting diversified personnel persist within organizations, including gender predominance in certain sectors and the absence of an inclusive organizational culture. While AI can be useful and facilitative in the process, particularly for processing a large number of applications, professional judgment is still recommended to move towards an inclusive hiring process and workforce diversification. The still timid use of AI systems is based on fears and some mistrust, and the biases that it is also likely to generate. The results therefore confirm the gap between the use of AI tools in HRM practices and the state of scientific knowledge.
Keywords: Intelligence artificielle (IA), diversité, recrutement, sélection, dotation
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102230.More information
This research aimed to prepare guidelines for authors by investigating forms and functions of keywords assigned by authors in theses and dissertations defended in 2023 in the Graduate Program in Information Science at Unesp. The exploratory and descriptive study utilized a sample collected in the Unesp Institutional Repository. A corpus of 31 theses and 14 dissertations submitted to the Unesp Institutional Repository comprised a total of 183 keywords in Portuguese without duplicates and an average of 4.7 keywords, considering 213 keywords with duplicates. The analysis results initially identified that the Repository has a tutorial on using the Unesp Thesaurus to control vocabulary and that the authors use natural language to assign keywords. The findings reveal that, out of the 183 keywords, 89 (48%) are exclusive, singular and specific to the area of Information Science, candidates for descriptors in the Unesp Thesaurus. The other 94 keywords (51.3%) have 40 (21.3%) exact descriptors, and the other 54 (29.5%) present forms and functions that serve as examples for inclusion in the tutorial instructions. Based on the results obtained, it is concluded that the percentage of 21% overlap between keywords and descriptors reveals that the Unesp Thesaurus was consulted by the authors when filling out keyword metadata and that the low number of exact descriptors and exclusive keywords indicate that they need to be included as new terms. It is recommended, therefore, to define an Indexing Policy that considers the need for hybrid coexistence between natural language and vocabulary control.
Keywords: Theses and dissertations, Thèses et mémoires, Keywords, Mots-clés, Mots-clés fournis par l'auter, Author-supplied keywords, Vocabulaires contrôlés, Controlled vocabularies, institutional repository