Toward Achieving Health Equity – ASPO's 2022 Annual Meeting March 13–15, 2022 Marriott University Park, Tucson, Arizona
Bibliographic record
Abstract
Communities of color, and people who are low income, rural, LGBTQ+, immigrants, and Indigenous, among others, face disproportionate and inequitable cancer burden. While advances in prevention and control research have led to improvements in cancer incidence and better survival from cancer overall, U.S. cancer inequities persist, and for some populations, gaps have widened over time. As highlighted in the 45th ASPO meeting in March 2021, there is an increasing acknowledgement for the impact of structural racism and discrimination as fundamental causes of these cancer inequities.To further advance the productive discussions from the 2021 ASPO meeting, the theme of the 46th ASPO meeting will be Towards Achieving Health Equity and will feature novel approaches to addressing cancer health inequities. The program committee was selected for their commitment and expertise in key areas of cancer health inequities. Working closely with the program committee, we organized a thought-provoking meeting to highlight emergent approaches and opportunities to address cancer inequities. Four symposia are planned on the topics of: (i) cancer interception: from concept to clinic; (ii) innovations in patient navigation: what's it going to take to achieve cancer equity? (iii) convergence epidemiology: bridging omics with social determinants and structural factors; and (iv) resituating cancer control within public health and communities. This year, we have also planned an additional panel discussion on institutional approaches for addressing diversity, equity, and inclusion, and concurrent sessions on novel approaches of and bias considerations in using electronic health records data in cancer control research, and challenges and successful examples in cancer consortia. The final program is shaping up with prestigious scholars in each of these topics already confirmed.Call for abstracts is now active and the highest scoring abstracts will be selected for oral presentations at the virtual conference and we will also have, as usual, best poster awards. Meeting registration is now open.ASPO's Annual Meeting will be held Sunday, March 13 – Tuesday, March 15 at the Marriott University Park in Tucson, Arizona. The Associate Director and Program Leader Workshop will be held on Sunday, March 12. More information is available at www.aspo.org.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.095 | 0.023 |
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 source (direct Gemma or distilled Codex), 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".