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Enregistrement W4400459290 · doi:10.1002/lob.10648

2024 <scp>ASLO</scp> Business Meeting and Membership Highlights

2024· article· en· W4400459290 sur OpenAlexaboutno aff
Dianne I. Greenfield

Notice bibliographique

RevueLimnology and Oceanography Bulletin · 2024
Typearticle
Langueen
DomaineDecision Sciences
ThématiqueAcademic Publishing and Open Access
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésBusiness administrationBusiness

Résumé

récupéré en direct d'OpenAlex

The year 2023 was characterized by an overall membership decrease. As of 31 December 2023, there were 3047 ASLO members. This is a drop of 117 (−3.7%) people since 2022 and continues a 3 year consecutive decline such that 2023 had the lowest membership since 1984. All membership categories either lost numbers or remained unchanged, except Early Career (+15 numbers, +2.8% relative to 2022). The gain in Early Career members helped offset the 2022 loss (−147) within that category. However, the distribution of membership categories remained fairly consistent as Regular (39%), Student (30%), Early Career (18%), and Emeritus (5%). Other membership types (Life, etc.) were <5% of our total membership/category. Despite the decline in overall numbers, ASLO made exciting gains in new members. During 2023, ASLO welcomed 1050 people to our society, a substantial increase (+581, +123.9%) over new members in 2022. Nearly half (49%) of those who joined were students, and our European membership rose by an impressive 12% relative to 2022 (Fig. 1) from the 2023 ASM being held in Mallorca, Spain. In fact, the United States' proportional membership dipped <50% for the first time in ASLO's history, underscoring the international importance of our Society. While North America (USA + Canada + Mexico) remains the majority (55.9%) of members, other regions (≥1% of membership) included Africa (3%), Asia (18%), Central and South America (3%), the Middle East (1%), and Oceana (3%). The United States had the highest total numbers, followed by Canada, Germany, Spain, Japan, Sweden, and the United Kingdom. Spain's membership increased by 120% (119 members in 2023) as the ASM host country. However, renewals decreased (−25.9%) such that each membership category had fewer renewals than 2022. Retention was 63.1%, a decline from the 76% of the previous year. Regarding membership composition, (80%) described their primary scientific field as oceanography (44%), limnology (30%), and both oceanography and limnology (26%), similar to last year, with a 1% exchange between limnology (−1%) and both (+1%). Members continue to describe themselves as multidisciplinary spanning biology (2141), chemistry (1007), geology (298), optics (188), and/or physics (408). In 2023, 83% shared their gender identity as male (51%), female (48%), nonbinary (0.5%), and preferred not to say (<0.5%). This led to the largest % of people identifying as female since ASLO began asking about gender identity. In summary, although ASLO's membership numbers have been declining, our diversity is growing. ASM positively influenced geographic breadth, especially within our European membership. We must identify strategies that are targeted to each membership category, as well as increase our focus on Regular members (e.g., Mid-Career+). ASLO has been discussing ideas such as improved networking and implementing membership benefits/recognitions for people who have been with ASLO on both short and long-term time scales. ASLO's Board continues to explore ways we can grow our diversity, and we welcome your ideas. The Board remains optimistic about ASLO's long-term trajectory. Please reach out and learn about the many ways in which you can actively participate in our wonderful society (publications, committees, webinars, outreach, and many others). I hope to see you all next March in Charlotte, North Carolina. Dianne I. Greenfield, Ph.D. ASLO Secretary [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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,004
score de la tête « metaresearch » (Gemma)0,003
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCommunication savante
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,116
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0040,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,002
Études des sciences et des technologies0,0000,001
Communication savante0,0020,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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 Opus0,033
Tête enseignante GPT0,306
Écart entre enseignants0,273 · 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 tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

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
Publié2024
Routes d'admission1
Résumé présentoui

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