Mapping the Infoscape of LIS Courses for Intersections of Health-Gender and Health-Sexual Orientation Topics
Notice bibliographique
Résumé
IntroductionHealth information support services are essential in today's society and it is urgent that their development, provision, and delivery reflect progressive cultural values in the 21st century (Braa, Monteiro, & Sahay, 2004; Mehra & Dessel, 2011; Saxena, Thomicroft, Knapp, & Whiteford, 2007). This is especially true regarding gender and sexual orientationrelated content (e.g., information needs, values, and practices) that is considered taboo owing to patriarchal norms and heterosexist assumptions all-pervasive in our society and culture (Lugg, 2003; Reardon, 2001; Skelton, 2001). The intent of the article is to explore the information landscape (i.e., infoscape) of library and information science (LIS) courses for intersections of health-gender and health-sexual orientation topics, concerns, and issues.The strategy of to study the infoscape that LIS programs create via the public domain of the Internet in representing information about the courses they offer on their websites is explored. The Merriam-Webster Dictionary (2004) defines the term mapping as the act or process of making a and identifies the following meanings of a map: as something that represents with a clarity suggestive of a (noun); to plan in detail (transitive verb); and to assign in a relation or connection to another (intransitive verb) [italics added]. These meanings of have been applied in LIS to represent: a conceptual analysis of disciplinary domains (e.g., science) (Klavans & Boyack, 2009); tools for understanding of information-related patterns in software development and use in various areas (Cobo, Lopez-Herrera, Herrera-Viedma, & Herrera, 2011); methods to create local, regional, and global maps (Klavans & Boyack, 2011); and, techniques to represent bibliometric research (Nees, Waltman, Dekker, & Berg, 2010; van Eck, Waltman, Dekker, & van den Berg, 2010). This article adopts the term map in its conceptual meaning from popular vernacular and integrates its various dimensions (identified above) to just mean organizing or systematizing information in a way that reveals trends and patterns in a collection of LIS courses. The concept of LIS is used with reference to the entire gamut of information creationorganization-management-dissemination processes and their education in the contemporary context.The term infoscape (etymology = info + scape) refers to the virtual and physical landscape of information and its interactions (Skovira & University, 2004). Mapping the infoscape of LIS course representations on the web (as conducted in this research) is important for identifying the patterns and course counts to track the intersections of health-gender and healthsexual orientation topics in the LIS curricula across the master's degree programs in Canada and the United States. The concept of infoscape helps holistically relate to an informational ecology or the environment of information use and information creation from the enterprise level to the personal level (in this case from the programmatic level in the LIS schools to the individual course level) (Davenport & Prusak, 1997; Hasenjager, 1996; Nardi & O'Day, 1999). Documenting the public representations of courses on the websites of LIS programs is significant since the Internet has now become unequivocally the primary information resource tool used by diverse populations in nearly every part of the world (Leu, Kinzer, Coiro, & Cammack, 2004; Peterson & Fretz, 2003; Rice, 2006). It is often the first place where potential students and other stakeholders will search and find information about LIS programs (Johnson, 2007; Manzari & Trinidad-Christensen, 2006). Analyzing what LIS programs are doing (or not doing) in representing information about their programs on the publicly accessible online domain can potentially identify marketing and public relations strategies for the profession as a whole, and by individual programs, to showcase their offerings and attract the best of students to their ranks (Kim & Sin, 2006; Wilde & Epperson, 2006). …
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 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 | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,006 | 0,012 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,007 | 0,005 |
| Science ouverte | 0,000 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,027 | 0,002 |
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 ».