Dialectic narratives, hostile actors, and Earth’s resources in Saskatchewan, Canada
Bibliographic record
Abstract
This paper uses networks of action situations (NAS) together with actor network theory (ANT) to identify the decisions that were made in Saskatchewan regarding power production and explore what future choices are available in the context of climate change. A theoretical and methodological contribution to NAS literature is made with focus on interconnected human and non-human objects (carbon, hydro, and uranium) or 'actants' and the development of discourses supporting or opposing their development. Actants provide the nodes of focus, while discourses explain the development of actants and their links. Identification and explanation of the emergence and recession of actants on the Saskatchewan landscape are analyzed with diagnostics of telecoupled systems, polycentric governance, and flows of faction situations. Focus group and survey data are used to identify future pathways and imaginaries of power production and the actants of carbon, hydro and uranium. Actants of carbon (coal) and hydro are possibly kept alive with carbon capture and storage and import of hydro-electricity from the distant action situation in a neighboring province (if the necessary infrastructure is built). While actants of renewables are strongly emerging, uranium currently mined on the Saskatchewan landscape is receiving strong support by government due to the possibility of small modular reactors (SMRs). This expanded theoretical conception of NAS illustrates distant action situations impact on local narratives and decision-making and dynamics of polycentric governance that are neither top down nor collaborative. Supplementary Information: The online version contains supplementary material available at 10.1007/s11625-022-01214-y.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.018 | 0.008 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".