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Enregistrement W2549419161 · doi:10.1111/geb.12546

In the company of greatness: announcing the best reviewers and best associate editors

2016· article· en· W2549419161 sur OpenAlexaboutno aff
Brian J. McGill, María Dornelas, Richard Field

Notice bibliographique

RevueGlobal Ecology and Biogeography · 2016
Typearticle
Langueen
DomaineMedicine
ThématiqueHealth and Medical Research Impacts
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésGreatnessBest practiceSet (abstract data type)Service (business)Quality (philosophy)Public relationsPsychologyLibrary scienceHistoryPolitical scienceMedia studiesSociologyLawComputer scienceBusinessMarketingSocial psychologyEpistemology

Résumé

récupéré en direct d'OpenAlex

In our editorial in January 2016 (McGill et al., 2016), we announced our intention to give awards for ‘Best Reviewers’ and ‘Best Associate Editors’. Our thinking was that these roles are a lot of work, are critical to the journal, and are all too rarely recognized. We figured that by highlighting a few especially exceptional participants we could bring recognition to this role. Selecting just a few has not proved easy but we think it is important and we made the commitment, so here we announce the winners. At GEB, we try to look for ways to encourage good practice. We have decided to kick the reviewer and editor awards off with a double set of them, one for each of the last two years. Thus, one set of awards is for the period before we announced that there would be awards. We like the idea of rewarding altruism: people who do great service to the scientific community without any thought of being rewarded for it. We label the two time-periods 2014–2015 and 2015–2016 for convenience, though actually we had to go to press some months ago and operationally we are running an approximately July–June annual time-window from now on. We look forward to giving awards again for July 2016-June 2017 in the December 2017 issue of GEB. For the reviewer awards, we took into account the number and timeliness of reviews, consulted our Associate Editors on quality of reviews and checked out some of the reviews sent in by short-listed people. In the process we were reminded of what a great job many people do when reviewing for GEB. We, and the field in general, benefit greatly from thoughtful, constructive reviews from people who demand high standards and offer excellent suggestions about how to reach those heights. What these reviewers do reflects well on science and scientists. As is typical, there was a fair amount of inequity among reviewers. Some individuals frequently declined or did not answer invitations to review and yet continued to publish in GEB1. And of course there was a long tail of hundreds of individuals asked only once or twice. But other individuals were asked many times and accepted many times. Although most of these will not receive rewards, they are critical to our journal and we thank them annually as we do in this issue. And did so with great insight and quality. Recognizing this behaviour is in a nutshell is why we want to offer these rewards. It rapidly became clear that pulling out a few names from a long list of people who have provided great service is difficult. We have undoubtedly not rewarded some of our excellent reviewers. In the process of deciding on the award winners, we have however sent a long list of many dozens of names of noteworthy reviewers to more than 50 experts in our field (our Associate Editors), associating those names with great work. We hope this may end up producing its own rewards for some of you, even if you are not named in this document this year. We also found it difficult to decide the Associate Editor awards. We interact regularly with the editors, and did not need to do an information-gathering exercise. We compared thoughts between the three of us and also David Currie, the Editor-in-Chief until 2015. Choosing was especially challenging because, by definition, our associate editors are a select group who all do excellent work. The three people listed below have been outstanding for years, and all have served as GEB editors since 2011 or before. Thus duration of service proved a major criterion in these inaugural awards. The main message, though, is that we are extremely grateful for the superb work done by our entire body of Associate Editors. We are privileged to work with you all. To briefly grab your attention for another topic, we are pleased to report some other developments of GEB. In particular, we have recently published new author instructions, so please check them out. Among the changes is the introduction of a new type of paper, the data paper where we publish short summaries that introduce noteworthy data sets. To make clear that GEB welcomes papers distinguished by covering large spatial, taxonomic and/or temporal scales, we now require the structured abstract to contain short statements of coverage across all three of these scales. We have also upped the expectation for data sharing and publication, though we have held back from making it an absolute requirement. We now expect you to make the data publicly available, or else give a clear statement of why this was not possible. We are extremely grateful for all the hard work by hundreds of reviewers and dozens of associate editors that goes into our journal. They are the heart and soul of what makes our journal great. And we are not only immensely grateful but have genuinely enjoyed working with and learning from these scientists. And we can't wait to recognize more people next year! Brian J. McGill1, Maria Dornelas2 and Richard Field3 1University of Maine, School of Biology & Ecology and Mitchell Center for Sustainability Solutions, Orono, Maine, USA E-mail: [email protected] 2University of St. Andrews, St. Andrews, Fife, United Kingdom E-mail: [email protected] 3University of Nottingham, School of Geography, Nottingham, UK E-mail: [email protected]

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,089
score de la tête « metaresearch » (Gemma)0,292
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesaucune
DomaineSignal candidat: Évaluation · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,911
Score d'incertitude au seuil0,471

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0890,292
Méta-épidémiologie (sens strict)0,0020,002
Méta-épidémiologie (sens large)0,0030,002
Bibliométrie0,0050,004
Études des sciences et des technologies0,0100,010
Communication savante0,0430,023
Science ouverte0,0070,008
Intégrité de la recherche0,0210,037
Charge utile insuffisante (le modèle a refusé de juger)0,0150,022

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.

Tête enseignante Opus0,044
Tête enseignante GPT0,357
Écart entre enseignants0,313 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Devis d'étudeSans objet
DomaineÉvaluation
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2016
Routes d'admission1
Résumé présentoui

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