The value and broader impacts of agricultural and environmental scientific meetings
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The socioeconomic value of content presented at the ASA‐CSSA‐SSSA (where ASA‐CSSA‐SSSA is American Society of Agronomy–Crop Science Society of America–Soil Science Society of America) Annual Meetings from 2014 to 2023 is estimated at $64.2 billion and is presented in this commentary as a thought exercise, highlighting the potential scale of research dissemination in scientific meetings. Scientific meetings are instrumental for propelling the quality and advancement of research via fostering timely feedback, knowledge dissemination, fresh perspectives, stimulation for networking and new collaborations, preparing scientists for public engagement, and addressing contemporary challenges of cultural accessibility and opportunity. Additionally, the broader impacts include near‐term benefits to agricultural and environmental scientists that can transform careers and perspectives on the world, especially for students and early career members. The benefits from these impacts on scientists are then anticipated to propagate into broader and longer term positive impacts on humanity worldwide. In this commentary, we offer the above as a provocation to spark peer discussion on evaluating scientific meetings’ contributions, alongside a working list of broader impacts to inspire philosophical and methodological innovations for quantifying their value.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it