Bibliographic record
Abstract
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]
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".