Disaster, displacement and justice: Powers and Faden’s theory of social justice and the obligations of non-governmental organizations towards Internally Displaced Persons
Bibliographic record
Abstract
Disasters have major impacts on populations, disrupting people's lives and exposing them to harm and, potentially, injustice.A range of actors, including national and international non-governmental organisations, provide assistance to victims of disasters.Initial disaster relief efforts primarily focus on saving lives.As the response progresses, efforts to promote recovery for individuals and communities affected by disaster become increasingly important.Given the heightened vulnerability and widespread needs of populations affected by disaster, choices must be made regarding which services and programs will be prioritized at each stage of the response.In consequence, questions of equity and justice arise related to these decisions, particularly as the acute crisis abates and a range of assistance programs aimed at promoting recovery is considered.The nature of these justice considerations and their implications for disaster response programs has received limited discussion in the literature.In this paper, we consider the potential contribution of Powers and Faden's theory of Social Justice for clarifying justice-based responsibilities of non-governmental organizations towards populations displaced within their own country by a disaster, and contrast it with the Basic Needs Approach widely used by humanitarian organizations.According to Powers and Faden, justice requires that a minimally sufficient level of well-being be secured for individuals who are systematically disadvantaged.We argue that this conception of social justice can help direct attention to diverse dimensions of well-being, and orient program planning in situations where non-governmental organizations work with internally displaced populations post the acute crisis of the disaster response.
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.036 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".