Bibliographic record
Abstract
Why is British Columbia unique within Canada? What are the physical processes that have made this province so rugged and that have produced such wonderful variation in climate and vegetation? Why did non-Natives come to British Columbia and what impact did they have on First Nations? Why were there so few treaties inthis province? Why did so many Asians come to this province and then leave for other parts of Canada, or return home? How were resources developed in the past and how are those resources developed today? British Columbia has a rich and varied resource base. Forestry fishing, mining, energy, agriculture and tourism are discussed in terms of their physical characteristics, historical development, and present day importance to the province. For many of these resources the legacy of exploitation and poor management has been the basis of present day crises. Other resources, such as tourism, are steadily increasing, bringing employment and growth to some regions more than others and often running into conflict with the long established extractive industries. The book is divided into two parts. The first focuses on processes of change and development to the landscape and the people of British Columbia and examines natural hazards, physical processes, European historical geography, First Nations peoples, and Asian immigration. The second part contains a detailed examination of the economic geography of the province, as well as addressing the present-day issues of urbanization, economic development, and resource management.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.036 | 0.004 |
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".