Physicists and Astronomers Use Google as a Starting Point for Specific Queries, but Do Not Intentionally Use It to Search for Articles
Notice bibliographique
Résumé
A Review of: Jamali, H. R., & Asadi, S. (2010). Google and the scholar: The role of Google in scientists' information seeking behaviour. Online Information Review, 34(2), 282-294. Objective – To determine how Google’s general search engine impacts the information-seeking behaviour of physicists and astronomers. Design – Using purposive stratified non-random sampling, a mixed-methods study was conducted which included one-on-one interviews, information-event cards, and an online questionnaire survey. Setting – Department of Physics and Astronomy at University College London. Subjects – The researchers interviewed 26 PhD students and 30 faculty members (23% of the department’s 242 faculty and students), and 24 of those participants completed information-event cards. A total of 114 respondents (47.1% of the department members) participated in the online survey. Methods – The researchers conducted 56 interviews which lasted an average of 44 minutes each. These were digitally recorded, fully transcribed, and coded. The researchers asked questions related to information-seeking behaviour and scholarly communication. Four information-event cards were given to volunteer interviewees to gather critical incident information on their first four information-seeking actions after the interview. These were to be completed preferably within the first week of receiving the cards, with 82 cards completed by 24 participants. Once initial analysis of the interviews was completed, the researchers sent an online survey to the members of the same department. Main Results – This particular paper examined only the results related to the scholars’ information-seeking behaviour in terms of search engines and web searching. Details of further results are examined in Jamali (2008) and Jamali and Nicholas (2008). The authors reported that 18% of the respondents used Google on a daily basis to identify articles. They also found that 11% searched subject databases, and 9% searched e-journal websites on a daily basis. When responses on daily searching were combined with those from participants who searched two to three times per week, the most popular method for finding research was by tracking references at the end of an article (61%). This was followed by Google (58%) and ToC email alerts (35%). Responses showed that 46% never used Google Scholar to discover research articles. When asked if they intentionally searched Google to find articles, all except two participants answered that they do not, instead using specific databases to find research. The researchers noted that finding articles in Google was not the original intention of participants’ searches, but more of a by-product of Google searching. In the information-event card study, two categories emerged based on the kinds of information required. This included participants looking for general information on a specific topic (64%, with 22 cases finding this information successfully), and participants knowing exactly what piece of information they were seeking (36%, with 28 cases finding information successfully). There was no occurrence of using Google specifically to conduct a literature search or to search for a paper during this information-event card study, although the researchers say that Google is progressively showing more scholarly information within its search results. (This cannot be ascertained from these specific results except for one response from an interviewee.) The researchers found that 29.4% of respondents used Google to find specific pieces of information, although it was not necessarily scholarly. Conclusion – Physics and astronomy researchers do not intentionally use Google’s general search engine to search for articles, but, Google seems to be a good starting point for problem-specific information queries.
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 | 0,008 | 0,055 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,019 | 0,025 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,007 | 0,014 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,029 | 0,017 |
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 ».