Replication Data for: Canadian Community and Co-Operative Energy Database (CCED) Co-Operative Energy Map Layers
Bibliographic record
Abstract
This dataset consists of the tabular data files used to create a database of energy activities led by co-operatives, the Canadian Community and Co-operative Energy Database (CCED). The CCED and the map it enables, the Canadian Renewable Energy Co-operative Map, extends the analysis of energy activities done by Fezulla, Pare, and Parkins' 2024 Canadian Renewable Energy and Battery Storage Map (CREBS) project. The CCED builds on existing outdated or more narrowly focused datasets of Canadian energy co-operatives, extending beyond power generation to grid ownership, electricity retailing, and installation of energy equipment for demand management and efficiency purposes. These key sources of data included the 2023 Census of Renewable Energy Co-operatives (Leonhardt, R., Pigeon, M.-A., & Boucher, M. 2022) which focused only on generation co-operatives but not the range and location of projects across Canada. It also included the outdated datasets in MacArthur (2016) and MacArthur and Hoicka (2018), and more geographically focused (Ontario) data from Tarhan (2025). The CCED updated and supplemented these existing datasets, classifying entries based on the primary activities and geographic location. Additional data sources included the Ontario Feed-in Tariff Program awarded projects data, the Nova Scotia Community Feed-in Tariff Program project data, the Bullfrog Community Projects website, the Federal Clean Energy for Rural and Remote Communities (CERRC) initiative, Community Energy Co-operative Canada (CECC), and online research based on Co-operatives and Mutuals Canada data. More detail on the data sources and gaps is outlined in the methodology section below. The entries in the CCED database that were active as of March 2025 were mapped using ArcGIS Online to the Canadian Renewable Energy Electricity Co-operative Map, which shows the key projects and activities undertaken by co-operatives in the energy section. The names of the map layers created, Co-Operative Renewable Electricity Generation and Other-Co-operative Energy Activity, correspond to the names of the data files found in this dataset. Methodology and data sources, including information on data gaps, can be found in the included PDF.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.016 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.102 | 0.056 |
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".