La recherche bibliographique en médecine et santé publique: guide d’accès
Notice bibliographique
Résumé
I recently read a novel set in an American college in which the author made numerous references to the main characters “googling” for information or having “googled” for all the research on their latest assignment. With the web so readily available, one might raise the question of why a book aimed at medical and public health researchers on recherche bibliographique (bibliographic searching) is needed, and one in French at that? Now that students and researchers have Google, or better yet the recently released beta version of Google Scholar, to find all the public health information on the web, why would anyone need something as old-fashioned as a book on bibliographic searching? Just enter a few keywords into any search engine and you have an unlimited amount of information at your fingertips (meme en francais). I would argue the need is probably greater now than ever before for a book on organized systematic searching. While huge depositories of information are readily available through a basic computer search, it is not always the best or most complete information. The temptation is to take what is available with just a few clicks on your mouse versus a visit to a library for a book or a journal article, or doing an in-depth and informed search. Researchers in the area of medicine and public health, however, need to be able to locate the most up-to-date, relevant and evidence-based information possible. To obtain this information requires a systematic methodology for attacking the huge amount of health literature and assuring that all the major and important sources are queried in order to obtain the best information Evelyn Mouillet has written a simple and well-laid-out guide for searching medical and health literature in a straightforward manner. The book begins with a discussion of how to search the basic sources. While basic searching need not be complex, it does require the kind of systematic approach which Mouillet presents in this book. She progresses through the major French-language health resources and then covers international sources (almost exclusively English). Important medical databases such as PubMed are covered with a clear explication of the differences between MEDLINE and PubMed. Also covered are bibliographic management software with emphasis on EndNote. The guide is made even more user-friendly by its inclusion of many illustrations and visual guides that mimic the computer screen during a search. Is there truly a need for guide such as this in French? Having covered the A to Z language spectrum, where I conducted library training sessions for an Albanian-speaking-only audience via a French interpreter, and having used Vietnamese versions of WHO publications during a library presentation, I welcome any documentation to assist in teaching researchers how to conduct in-depth searching. While the majority of the resources may be in English or use an English interface, it is beneficial for non-Anglophones to have access tools in their maternal language. Basic concepts of Boolean searching are better learnt in one’s most conversant language, and my personal observations over ten years of teaching reinforce this belief. A couple of changes would improve further editions. A stronger chapter devoted to defining the research question would make the book more useful to medical and public health researchers. As a librarian, my most important contacts with researchers are spent defining and probing their research questions, a step which involves breaking the question down into its various components. This vital step helps to determine which resources will be used and the breadth of resources to be searched. An overly broad question can lead to the frustrating situation of bringing up literally tens of thousands of hits. Refining the question allows for a more manageable number of articles, perhaps including the article that has already summarized and evaluated the best information from all those other articles. I also noticed a definite preference for resources located within France. This ignores the rich resources of Francophone research outside of France, including Belgium, Canada, Switzerland and Francophone Africa, all of which offer relevant, high-quality research. Africa Index Medicus (AIM), for example, is a bibliographic database that indexes many Francophone African journals and reports, often with links to the articles’ full text. Sole reliance on the French databases, even with supplementation from PubMed and Embase, almost ensures that researchers will miss relevant research, because research from developing countries may not be indexed by the major databases or there can be significant delays from when the research is published until it appears in the major databases. Evelyne Mouillets’s book is, however, one of the better books to guide readers in searching for medical and health information that I have read. Hopefully the publisher will come out with a translation, as not only is it an excellent guide to searching, but it would also be useful to have an English version to encourage researchers to explore valuable French-language resources. ■
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 | 0,023 | 0,060 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,016 | 0,015 |
| Études des sciences et des technologies | 0,003 | 0,006 |
| Communication savante | 0,016 | 0,017 |
| Science ouverte | 0,003 | 0,006 |
| Intégrité de la recherche | 0,007 | 0,009 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,049 | 0,089 |
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 ».