Whose needs count in situations of forced displacement Revaluing older people and addressing their exclusion from research and humanitarian programmes
Bibliographic record
Abstract
Older people remain one of the most neglected, invisible, and marginalised groups among displaced persons, which is in part due to ageist stereotypes that persist and permeate the humanitarian system. Using a theoretical framework grounded in the capabilities approach, this article examines urban/protracted situations of displacement in developing countries and highlights gaps in the limited knowledge and assistance to older displaced persons that must be bridged in order to break the vicious cycle between research and policy that continue to marginalise older persons from humanitarian responses. At the heart of the issue around older peoples' exclusion and invisibility is their lack of voice in decision-making processes and their capacity to contribute to improving the programmes and policies that directly impact them. The paper thus also argues for the meaningful inclusion of older displaced persons in decision-making processes around programmes that concern them.
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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 | 0.001 | 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 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".