Culturally driven forest management, utilization and values : a Nuxalk First Nations case study
Bibliographic record
Abstract
The forests of British Columbia have been managed for thousands of years to provide a range of products and services. For the Nuxalk people of Bella Coola, BC, their forests were used to: build homes and canoes, act as a transportation system (grease trails), and provide material for clothing, fuel and cultural/artistic needs. These forests also provide a host of plants used for nourishment and medicine. With the arrival of Western cultures the lives of First Nations people have been dramatically altered; and from a First Nations perspective, these traditional goods and services have been eroded. Today they seek to restore and protect the forests which provide these goods and services, while at the same time recognizing the needs of a modern life which include: improved housing, energy that is environmentally friendly and the development of new products and services to sustain their economy. Over the past year a number of people from different disciplines came together at the University of British Columbia to assist the Nuxalk Nation by conducting a series of applied research projects (titles in bold). These included Exploring Forest Management Alternatives and developing options for addressing some of the key economic, environmental, social and cultural challenges. The projects developed to address these challenges included a number of energy projects that focused on Forest Biomass for Hot Water and Warm Houses, Energy from Wood Waste, and Sawdust Products: Briquettes and Biochar. Other economic development projects focused on markets for non-timber forest products such as those identified in An Essential Oils Plan and high value artisanal products that can be developed using advanced Manufacturing and Design Technology. To assist with social development, the UBC team focused on the inadequacy of residential and senior’s housing and plans were developed to provide Help and Housing for Those Who Need it Most, and culturally reflective designs were completed for a Solid Wood House Made in Bella Coola. The series of short articles which follow are a brief description of these projects. We do wish to thank the Nuxalk people for agreeing to work with us, and some major financial sponsors that made it possible: the Nuxalk Development Corporation, MITACS Research Funds and the Coast Opportunity Funds.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".