Engaging or Deterring the Next Generation? An Analysis of Fees for Cardiac Surgery Conferences
Bibliographic record
Abstract
Background: Conferences are valuable platforms for academic discourse. However, trainees, individuals with lower income backgrounds, and attendees from low- and middle-income countries (LMICs) often face significant financial barriers that may limit accessibility to conferences. This study evaluates fees for attending international cardiac surgery conferences to better understand potential financial barriers. Methods: Registration fees for 2022-2023 international cardiac surgery conferences were analyzed. Fees were categorized on the basis of the career stage and society member status of the attendee. Other data collected included the meeting's subspecialty, location, availability of discounts, and virtual components. Results: Seventeen conferences were identified. Discounts are widely available for students, residents, and fellows attending cardiac surgery conferences in 2022-2023. Society member students' fees ranged from US $0 to $390 (median, US $15; interquartile range [IQR], $0-$198). Society member residents' and fellows' fees ranged from US $0 to $795 (median, US $200; IQR, $75-$390). Society member staff's fees ranged from US $200 to $802 (median, US $545; IQR, $441-$608). Four conferences (23.5%) explicitly mentioned discounts for LMIC attendees, whereas 5 conferences (29.4%) mentioned virtual components. Conclusions: Conference fees remain substantial for trainees and LMIC participants, who are respectively burdened with tuition costs and lower incomes and purchasing powers. Conferences should explore avenues to reduce financial barriers to provide more equitable opportunities for current and future generations of cardiac surgeons.
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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 | 0.010 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".