Bibliographic record
Abstract
Fort St. James has long been a one industry, forestry-based community. Throughout the years, Fort St. James has always been able to ride out the storms and survive economic downturns. However, the storm created by the Mountain Pine Beetle epidemic has severely impacted the forest industry and its reliant communities. The evidence can be seen in the Fort St. James community, with two mill closures, which in turn resulted in an increasing number of business closures, home foreclosures, and boarded-up buildings. The parking lots that were once filled are now empty. It has been estimated that half of our workforce is currently unemployed. People are now forced to seek work outside of the community in order to support their families, or the whole family is relocating outside of Fort St. James. Over the years, the swings in the economy or industry have substantially impacted various communities within Canada. However, many of these communities have rebounded successfully. The World Tourism Organization (UNWTO) website www.unwto.org indicated the tourism sector has been more resistant to the economic downturn than other sectors. In fact, the UNWTO believes that international tourism will almost double by 2020. Overnight travel from overseas countries reached a high of 4.5 million trips in 2008, up 2.1% from 2007. This was the fifth consecutive increase in overseas travel to Canada. Since falling 16.0% in 2003, overnight travel from overseas countries has increased 41.0% ...These growing numbers provide pressure for all communities within B.C. to strategize to try to acquire a piece of the tourism market. According to BC Stats, British Columbia's tourism industry accounted for approximately $6.6 billion of its GDP in 2008 ...These figures are promising for communities such as Fort St. James beginning to position themselves within the tourism industry. This project examined the current resources and evaluated trends available within the tourism industry in Canada, BC, Nechako Bulkley Region, and Fort St. James. This pro
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.083 | 0.012 |
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".