Unintentional Influence: Exploring the Relationship between Rural Regional Development and Drinking Water Systems in Rural British Columbia, Canada
Bibliographic record
Abstract
Rural drinking water systems face a number of challenges, not the least of which is a growing infrastructure deficit. While age and investment are typically highlighted as key factors influencing the infrastructure deficit, other pervasive challenges remain for rural drinking water systems in British Columbia, Canada. This raises the question of whether factors influencing the infrastructure deficit extend beyond those typically captured in the literature. The purpose of this paper is to examine the relationship between rural regional development and drinking water systems in order to provide a historically and theoretically informed lens on the relationships between the two and how these links influence present day challenges. The authors aim to temper the presentism that often characterizes current debates surrounding the infrastructure deficit and to frame current drinking water system challenges within a more contextually-informed and regionally integrated framework. Keywords: drinking water; infrastructure; staples theory; rural; regional development
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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 | 0.002 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".