Assessing Representation and Perceived Inclusion among Members in the Society for Epidemiologic Research
Bibliographic record
Abstract
Using web-based survey data collected June - August 2018 from the Society for Epidemiologic Research (SER) members, we characterized numerous dimensions of social identity and lived experience, and assessed relationships between these characteristics and perceptions of inclusion and society participation. We quantified associations between characteristics, feeling very welcomed, high (top 25th percentile) self-initiated participation, and any (top 10th percentile) society-initiated participation. Racial/ethnic and religious minority categories were blinded to preserve anonymity and we accounted for missing data. Most 2018 SER members (n = 1631) were white (62%) or female (66%). Females with racial/ethnic non-response were least likely, while white males were most likely to report feeling very welcomed. Members who did not report race, identified with a specific racial/ethnic minority, or were politically conservative/right-leaning were less likely than white or liberal/left-leaning members to have high self-initiated participation. Women and individuals of a specific racial/ethnic minority or minority religious affiliations were less likely to participate in events initiated by the society. These data represent a baseline for assessing trends and the impact of future initiatives aimed at improving diversity, inclusion, representation and participation within SER.
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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 | 0.068 | 0.017 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".