Notice bibliographique
Résumé
The Editors' Report Andries W. Coetzee, Editor and John Beavers, Co-Editor [The following is a slightly modified and updated version of the report made verbally to the LSA membership at the virtual annual meeting, on January 4, 2021.] In spite of the disruption caused by the COVID-19 pandemic, 2020 was another successful year at Language, during which we maintained a good submission record and a good time-to-decision. It was also a time of transition in the editorial team—we said goodbye to several members of the team, and also welcomed new members. We appreciate the continued support of the linguistics community for Language and for the work that we do as an editorial team. It takes the whole community to maintain Language as one of the prime publication venues in linguistics. 1. Impact of COVID-19 on language Although operations at Language were impacted by the COVID-19 pandemic, we were able to publish all four issues for 2020 on time, and we are also similarly set for at least the first two issues of 2021. This is in no small part due to the dedication of the members of the Language editorial team and to referees who made time to prepare reports even as they were dealing with significant increases in workload and family care responsibilities. We express our deep appreciation to the linguistics community for their continued support of the LSA's publication program. The ways in which the pandemic has impacted operations at Language are reflected in a slight decrease in the number of submissions (most likely due to authors having less time to dedicate to research) and a small increase in the time-to-decision (due to referees and editorial team members needing more time to complete tasks) compared to 2019. Although the effects did not impact the publication schedule for 2020, there is a possibility that some of the issues of 2021 may be a bit slimmer than usual. 2. Changes in the editorial team After three years as review editor, Lauren Squires (Ohio State University) stepped down from this position. Three associate editors cycled off from the editorial team at the end of their terms: Khalil Iskarous (University of Southern California), Lisa Travis (McGill University), and David Willis (Oxford University). Additionally, Shravan Vasishth also ended his service as associate editor during the course of 2020. We extend our appreciation to all of these individuals for their service to the LSA and the linguistics community. At the beginning of 2021, Jessi Grieser (University of Tennessee) joined the Language editorial leadership team as review editor. Toward the end of 2020 or the beginning of 2021 we were also joined by several new associate editors: Lisa Cheng (Leiden University), Anne-Michelle Tessier (University of British Columbia), Graeme Trousdale (University of Edinburgh), and Titus von der Malsburg (University of Potsdam). We look forward to working with these new members of the Language editorial team in the coming years. 3. Language by the numbers Volume 96 of Language consisted of four issues comprising 973 pages in the printed section, containing twenty-five research articles, one letter to the editor, and seventeen book reviews. The online sections of the volume had 343 pages, consisting of two articles in Teaching Linguistics, eight in Research Reports, one in Commentaries, and one target article in the Perspectives section, with seven responses. [End Page 432] During 2020, we received a total of 159 submissions. Table 1 shows the breakdown of submissions by journal section for 2020. The numbers from 2018 and 2019 are included for comparison. Click for larger view View full resolution Table 1. Submission by journal section for 2018, 2019, and 2020. For manuscripts submitted during 2020, the average time between submission and the various kinds of editorial decisions are given in Table 2 (with 2018 and 2019 included for comparison). Click for larger view View full resolution Table 2. Average number of days for various editorial decisions during 2018, 2019, and 2020. Starting in January 2019, authors indicate the primary field of their manuscript during the submission process, using the same categories as those used for abstract submissions to the annual meeting. Table 3...
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 | 0,015 | 0,097 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,004 | 0,002 |
| Études des sciences et des technologies | 0,003 | 0,002 |
| Communication savante | 0,016 | 0,007 |
| Science ouverte | 0,005 | 0,004 |
| Intégrité de la recherche | 0,009 | 0,009 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,176 | 0,177 |
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 ».