Are We Bridging the Research Practice Gap? (Editorial)
Notice bibliographique
Résumé
One of the key aims of Evidence Based Libraryand Information Practice is to bridge the research practice gap and make the findings of LIS research more accessible to library and information practitioners. I’ve therefore been keenly following the UK RiLIEs project(Research in Librarianship – Impact Evaluation Study; http://lisresearch.org/rilies-project/),which has been looking at ways to increase the impact of library related research for practitioners. The project culminated in a resources briefing(http://lisresearch.org/2012/07/10/research-intopractice-lis-research-resources-briefing/) whichI attended, and was thrilled to hear the project team report that the journal was one of the most appreciated sources of LIS research forpractitioners. My self-congratulation was alittle short lived, however, when the next set of findings presented was a range of resources that practitioners had heard of, but had yet to use – and sure enough, EBLIP was among them. Furthermore, other findings of the project included practitioners reporting a need for accessible summaries of research evidence!! The project team concluded that there was no shortage of research resources available to practitioners, but the challenge was finding the best way to make them available and easily accessible. As an open access journal, therefore, we need to work harder on publicizing the work we do. I’ve thus taken on board the recommendation that “here lies an opportunity for those with responsibility for freely available open access repositories of LIS research materials to raise awareness of their resources amongst the practitioner communities” (Hall, 2012). It is really important that as a journal we do take this message on board, as we have begun to find that the Evidence Summaries in EBLIP do make a difference. Over the past year, supported by a grant from the Canadian Association of Research Libraries, and led by our Associate Editor for Evidence Summaries, Lorie Kloda, we have been conducting a research project into the impact of Evidence Summaries. The project will be written up in full and the results published elsewhere, but in brief we validated a tool to assess the impact of the summaries on practitioners, used the tool to survey a number of Evidence Summary readers, and followed some of these up with more in-depth interviews. Initial results are promising, and we have found that Evidence Summaries impact on knowledge, individual practice, and more widely in the workplace of Evidence Summary readers. Earlier in the summer, we presented the results at a range of national (Canada and UK) and international conferences (in Europe and the US). Hopefully, these presentations (e.g., http://www.slideshare.net/lkloda/kloda-mla-2012-impact), will begin to further increase the awareness of Evidence Summaries – and perhaps turn some of that awareness into action. This issue sees a slight change in the Evidence Summaries, as described in Lorie’s editorial at the beginning of the Evidence Summary section. So, if you haven’t read an Evidence Summary before – I challenge you to read one today – and see if it makes a difference to your practice.
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 | 0,017 | 0,104 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,004 | 0,003 |
| Bibliométrie | 0,004 | 0,002 |
| Études des sciences et des technologies | 0,004 | 0,007 |
| Communication savante | 0,015 | 0,013 |
| Science ouverte | 0,007 | 0,003 |
| Intégrité de la recherche | 0,022 | 0,028 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,023 | 0,019 |
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 ».