Exposing the myths of household water insecurity in the global north: A critical review
Bibliographic record
Abstract
Abstract Safe and secure water is a cornerstone of modern life in the global North. This article critically examines a set of prevalent myths about household water in high‐income countries, with a focus on Canada and the United States. Taking a relational approach, we argue that household water insecurity is a product of institutionalized structures and power, manifests unevenly through space and time, and is reproduced in places we tend to assume are the most water‐secure in the world. We first briefly introduce “modern water” and the modern infrastructural ideal, a highly influential set of ideas that have shaped household water provision and infrastructure development over the past two centuries. Against this backdrop, we consolidate evidence to disrupt a set of narratives about water in high‐income countries: the notion that water access is universal, clean, affordable, trustworthy, and uniformly or equitably governed. We identify five thematic areas of future research to delineate an agenda for advancing scholarship and action—including challenges of legal and regulatory regimes, the housing‐water nexus, water affordability, and water quality and contamination. Data gaps underpin the experiences of household water insecurity. Taken together, our review of water security for households in high‐income countries provides a conceptual map to direct critical research in this area for the coming years. This article is categorized under: Human Water > Human Water
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".