Tracking Theory Building and Use Trends in Selected LIS Journals: More Research is Needed
Notice bibliographique
Résumé
Objective - The authors measure theory incidents occurring in four LIS journals between 1984-2003 in order to examine their number and quality and to analyze them by topic. A third objective, only identified later in the text of the study, was to compare theory development and use between Korean and international journals. Research questions asked include whether LIS has its own theoretical base as a discipline, and what characteristics the theoretical framework has. Design – Bibliometric study. Setting – Journal issues selected from four LIS journals for the time span from 1984 - 2003. Subjects – Two international journals, Journal of the American Society for Information Science and Technology (JASIST) and Library and Information Science Research (LISR) were selected based on their high ranking in the Social Sciences Citation Index (SSCI) impact factors. Two Korean journals, Journal of the Korean Society for Information Management (JKSIM) and Journal of the Korean Society for Library and Information Science (JKSLIS) were selected. Methods - After having determined a definition of theory, and identifying different levels of theory, the authors set up rules for the identification of theory incidents, which are defined as “events in which the author contributed to the development or the use of theory in his/her own paper” (550). Content analysis of 1661 research articles was performed to measure theory incidents according to working definitions. Interrater reliability was ensured by conducting independent coding for “subfield classification, identification of theory incidents, and quality measurement” (555), using a sample of 199 articles (random selection not specified), achieving 94-97% interrater reliability. Incidents, once identified, were evaluated for quality using Dubin’s “efficiency of law” criteria, involving measures of relatedness, directionality, co-variation, rate of change, and “profundity,” defined as the depth to which theory is incorporated into the research study. Main Results - 21.79% (n=362) of the articles contained theory incidents that were analyzed and evaluated. Trend measurement indicated an overall increase, although a slight decrease was shown in the year range 1993-2003. International journals accounted for 61.33% of theory incidents, compared to 38.67% for the Korean journals. T-testing showed that differences in means between Korean and international journals were not statistically significant. Topical theory areas were ranked by frequency. The top five areas were shown to be nearly identical between Korean and international journals. ANOVA was performed with significant results in the difference between efficiency ratings. Conclusion – The authors find that the overall proportion of theory incidents including both theory development and use increased through the 20-year time span examined, and that LIS has established its own theoretical framework based upon the frequency of incidents.
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 | 0,059 | 0,184 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,021 | 0,034 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,011 | 0,017 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».