Keeping communities at the centre of efforts to eliminate lymphatic filariasis: learning from the past to reach a future free of lymphatic filariasis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Since the launch of the Global Programme to Eliminate Lymphatic Filariasis (GPELF) in 2000, more than 910 million people have received preventive chemotherapy for lymphatic filariasis (LF) and many thousands have received care for chronic manifestations of the disease. To achieve this, millions of community drug distributors (CDDs), community members and health personnel have worked together each year to ensure that at-risk communities receive preventive chemotherapy through mass drug administration (MDA). The successes of 20 y of partnership with communities is celebrated, including the application of community-directed treatment, the use of CDDs and integration with other platforms to improve community access to healthcare. Important challenges facing the GPELF moving forward towards 2030 relate to global demographic, financing and programmatic changes. New innovations in research and practice present opportunities to encourage further community partnership to achieve the elimination of LF as a public health problem. We stress the critical need for community ownership in the current Covid-19 pandemic, to counter concerns in relaunching MDA programmes for LF.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 it