Can household water sharing advance water security? An integrative review of water entitlements and entitlement failures
Bibliographic record
Abstract
Abstract An increasing number of studies find that water sharing—the non-market transfer of privately held water between households—is a ubiquitous informal practice around the world and a primary way that households respond to water insecurity. Yet, a key question about household water sharing remains: is water sharing a viable path that can help advance household water security? Or should water sharing be understood as a symptom of water insecurity in wait for more formalized solutions? Here, we address this question by applying Sen’s entitlement framework in an integrative review of empirical scholarship on household water sharing. Our review shows that when interhousehold water sharing is governed by established and well-functioning norms it can serve as a reliable transfer entitlement that bolsters household water security. However, when water sharing occurs outside of established norms (triggered by broader entitlement failures) it is often associated with significant emotional distress that may exacerbate conditions of water insecurity. These findings suggest that stable, norm-based water sharing arrangements may offer a viable, adaptive solution to households facing water insecurity. Nevertheless, more scholarship is needed to better understand when and how norm-based water transfer entitlements fail, the capacity of water sharing practices to evolve into lasting normative entitlements, and the impact of interhousehold water sharing on intrahousehold water security.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".