2016 President's Plenary International Psycho-Oncology Society: challenges and opportunities for growing and developing psychosocial oncology programmes worldwide
Bibliographic record
Abstract
Consistent with the International Psycho-Oncology Society's (IPOS) vision and goals, we are committed to improving quality cancer care and cancer policies through psychosocial care globally. As part of IPOS's mission, upon entering "Official Relations" for a second term with the World Health Organization (WHO), IPOS has dedicated much attention to reaching out to countries, which lack formalized psychosocial care programmes. One of IPOS's strategies to accomplish this goal has been to bring psycho-oncology training programmes to low- and middle-income countries and regions. To this end, the IPOS Board approved a new position on the Board of Directors for a member from a low- to middle-income country (LMIC). The IPOS 2016 President's Plenary focused on challenges and opportunities that exist in growing and developing psychosocial oncology programmes worldwide. The plenary presentations highlight how IPOS and WHO have aligned their goals to help LMICs support cancer patients as an essential element of cancer and palliative care. IPOS country representatives are strongly supported in liaising with national health authorities and with WHO Country Representatives in LMICs. The plenary speakers discussed the role IPOS Federation has taken in building a global network of psychosocial leaders and the impact this had in assisting LMICs in meeting IPOS's psychosocial care objectives. The plenary highlighted the challenges of expanding psychosocial reach into these countries. One significant question remains: Can psychosocial guidelines be adapted to LMICs and regions?
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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.015 | 0.017 |
| Insufficient payload (model declined to judge) | 0.086 | 0.041 |
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".