Are Keynote and Invited Speakers at State Behavior Analytic Conferences Experts on Their Presentation Topics?
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 Board Certified Behavior Analysts® (BCBA®s) must acquire 32 continuing education units (CEUs) every two years. One way BCBAs obtain CEUs is by attending their state chapter conferences, which feature keynote speakers and invited speakers who disseminate information in their respective areas of presumed scientific expertise. This study evaluated 735 CEU presentations provided by keynote and invited speakers at state conferences in the United States for 2021, 2022, and 2023. For each keynote and invited presentation, researchers used Google Scholar to count the speakers’ (a) peer-reviewed publications on their presentation topic and (b) total peer-reviewed publications. In part, the results across all three years indicate that 31% of speakers had zero topic-specific publications. Notably, the percentage of speakers with zero topic-specific publications concerningly increased across the three years. Results also indicate nearly 40% of speakers with zero topic-specific publications did not have any peer-reviewed publications. We discuss the potential implications of the findings and suggest actions for offsetting the current trend.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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