Toward Understanding Power Dynamics in a Highly-Connected, Hyperlocal Coastal Decision Network (Bay of Fundy, Canada)
Bibliographic record
Abstract
This study highlights the unique characteristics of a hyperlocal, rural, coastal governance system. While social network analysis (SNA) is often used to identify power dynamics in a decision network, hyperlocal rural communities often have high social cohesion, which can result in a SNA showing a highly-connected social network, even if they do not necessarily engage in highly inclusive or equitable decision processes that these measures often indicate. In this case, high connectivity simply describes small-community social cohesion. SNA was conducted on questionnaire data, followed by qualitative interviews that helped to reveal nuances of socio-political power dynamics not evident from quantitative analysis. Interviews revealed that power dynamics may be related to mandated processes that determine which actors are included, but informal contact can change these dynamics. This study contributes to understanding power relations in hyperlocal systems by underlining the importance of using mixed methods in SNA to understand nuances of social dynamics.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| 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 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".