From “trust” to “trustworthiness”: Retheorizing dynamics of trust, distrust, and water security in North America
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
Assumptions of trust in water systems are widespread in higher-income countries, often linked to expectations of "modern water." The current literature on water and trust also tends to reinforce a technoscientific approach, emphasizing the importance of aligning water user perceptions with expert assessments. Although such approaches can be useful to document instances of distrust, they often fail to explain why patterns differ over time, and across contexts and populations. Addressing these shortcomings, we offer a relational approach focused on the trustworthiness of hydro-social systems to contextualize water-trust dynamics in relation to broader practices and contexts. In doing so, we investigate three high-profile water crises in North America where examples of distrust are prevalent: Flint, Michigan; Kashechewan First Nation; and the Navajo Nation. Through our theoretical and empirical examination, we offer insights on these dynamics and find that distrust may at times be a warranted and understandable response to experiences of water insecurity and injustice. We examine the interconnected experiences of marginality and inequity, ontological and epistemological injustice, unequal governance and politics, and histories of water insecurity and harm as potential contributors to untrustworthiness in hydro-social systems. We close with recommendations for future directions to better understand water-trust dynamics and address water insecurity.
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