Second Global Symposium on Health Systems Research: a conference impact evaluation
Bibliographic record
Abstract
Evaluation researchers have confirmed the importance of conference evaluation, but there remains little research on the topic, perhaps in part because evaluation methodology related to conference impact is underdeveloped. We conducted a study evaluating a 4-day long health conference, the Second Global Symposium on Health Systems Research (HSR), which took place in Beijing in November 2012. Using a conference evaluation framework and a mixed-methods approach that involved in-conference surveys, in-conference interviews and 7-month post-conference interviews, we evaluated the impact of the Symposium on attendees' work and the field of health systems research. The three major impacts on participants' work were new knowledge, new skills and new networks, and many participants were able to provide examples of how obtaining new knowledge, skills or collaborations had changed the way they conduct their work. Participants noted that the Symposium influenced the field of HSR only in so far as it influenced the capacity of stakeholders, but did not lead to any high level agenda or policy changes, perhaps due to the insufficient length of time (7 months) between the Symposium and post-conference follow-up. This study provides an illustration of a framework useful for conference organizers in the evaluation of future conferences, and of a unique methodology for evaluation researchers.
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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 | 0.027 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 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".