Notice bibliographique
Résumé
Snapshots of the Journal of Allied Health reveal profiles from the perspective of both production-related data and manuscript content. Shown below are data for the period May 1, 2013 to April 30, 2014.The Acceptance Rate figures are incomplete since of the 96 manuscripts submitted in that 12-month period, 30 of them (31.3%) still were pending. Some articles eventually will be accepted while others will be rejected. Consequently, the Acceptance Rate will change after a final decision either to publish or not publish is made for each manuscript. Research Notes manuscripts require the most time in the system from when they initially are submitted until a final decision is made. One reason for the longer period is that some items initially begin as Original Research manuscripts, but reviewers decide that it would be more appropriate to change their designation to the Research Notes category, which eventually requires more communication going back and forth among the parties involved.Similar to what occurs along a coastline, the Journal has both high tides and low tides. During the months of May to July in 2013, 35% of all manuscripts were submitted, whereas the months of January to March in 2014 accounted for only 17.7% of submissions. During that 1-year period, the United States accounted for approximately 72% of all manuscripts that were submitted. The next largest source was Australia, from which nearly 14% of manuscripts originated. The rest of the papers came from Canada, India, Iran, Jamaica, Kuwait, the Netherlands, Turkey, and the United Kingdom.During those same 12 months, 122 different reviewers were involved, representing 84% of invitees who accepted. Reasons for not participating usually stemmed from having too many other commitments at the time of the invitation or indicating that there was not suitable congruence between the topic of a manuscript and that individual's expertise. Among the group that conducted reviews, 51% did so on time, which means the initial assessment was done within a 30-day period. Several articles can go through as many three iterations, however, which explains the longer average amounts of time for the entire review process. Among reviewers who were unable to conform to the 30-day timetable for the first review, only 10% took more than 50 days.Given the wide-ranging nature of the various professions that fall under the rubric of allied health, it is not surprising that a great many different kinds of disciplines are represented in the manuscripts published in the category Original Research in the journal issues over the 5-year period from Summer 2009 to Spring 2014. The following professions were included: Audiology, Clinical Laboratory Science, Dental Hygiene, Emergency Medical Services, Nuclear Medicine Technology, Nutrition-Dietetics, Occupational Therapy, Physical Therapy, Physician Assistant, Radiologic Technology, Respiratory Therapy, and Speech-Language Pathology. The greatest number of manuscripts was on the topic of physical therapy, followed by occupational therapy, and physician assistant.The two largest kinds of topics covered in the manuscripts submitted were interprofessional education (not counting 12 papers that appeared in a Special Issue on that topic in Fall 2010) and studies involving students. Considerable overlap existed between the two categories, however, because many papers are based on an examination of various activities designed to expose students to notions pertaining to interprofessional education and practice. Other types of manuscripts had a focus on topics such as health disparities, student learning styles, patient behavior change, reflective thinking, faculty job satisfaction, and workforce retention.As editor, I believe the results demonstrate that the Journal of Allied Health reflects what is happening to an informative degree across many professions, involving the broad area of health professions education. Reviewers deserve a great amount of credit, not only for being willing to accept invitations to review manuscripts, but also to fulfill their assessment responsibilities in a high quality and timely manner. …
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 | 0,004 | 0,030 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,028 | 0,049 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,007 | 0,005 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,044 | 0,020 |
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 ».