Woody biomass-based bioenergy development at the Atikokan power generating station: local perceptions and public opinions
Bibliographic record
Abstract
To tackle climate change, reduce air pollution and promote development of renewable energy, the Ontario government is investing in the conversion of the coal-based Atikokan Power Generating Station (APGS) in Atikokan, Ontario, to woody biomass feedstock. This research offers one of the first looks at the perspectives of different individuals and groups on converting woody biomass to energy. Using a combination of study instruments which include literature review, surveys, interviews with key informants, semi-structured interviews, and focus group discussions, this dissertation uses qualitative research to provide a picture of the public?s opinions and attitudes towards the APGS biomass energy development. \nGiven Ontario?s huge and sustainably managed forest resource, woody biomass is expected to be a major component of renewable energy production in Ontario. The move towards renewable energy that replaces fossil fuels with woody biomass will have considerable socio-economic implications for local and First Nation communities living in and around the bioenergy power generating station. Findings indicate that there is wide support for biomass utilization at the APGS by local people, especially since the project would create sustainable employment. The connection of woody biomass-based energy generation and rural community development provides opportunities and challenges for Atikokan?s economic development. Respondents identified economic, environmental and social barriers to biomass utilization, and emphasized trust and transparency as key elements in the successful implementation of the APGS project. \nAs demand for woody biomass-based energy increases, special attention will be needed to ensure and maintain the social, economic and environmental sustainability of biomass use at the APGS. In this research, respondents? views about biomass utilization for energy mainly focused on forest-related issues rather than energy. In Atikokan much of the project?s social acceptability is directly linked to woody biomass providing job creation and community stability. Given this, it will be important to design policies and projects from a community development perspective to ensure long term community support. \nInformation provided by this research creates a base for discussions as forest biomass energy becomes a vital issue in Northwestern Ontario, Canada, and other regions of the world. This research provides a look at a community?s views using a method that provides breadth of information but that is specific in scope. Further research will be required to determine the reach of these opinions within the stakeholder groups, the general public, and across different regions.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".