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Record W4244412832 · doi:10.24124/2010/bpgub1464

Tourism strategies for Fort St. James

2010· dissertation· en· W4244412832 on OpenAlexaboutno aff
C. L. Smith

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsnot available
Fundersnot available
KeywordsTourismGeographyRecessionTRIPS architectureEconomyWorkforceWork (physics)Economic growthEngineeringEconomicsArchaeology

Abstract

fetched live from OpenAlex

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

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.747
Threshold uncertainty score0.504

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0060.001
Scholarly communication0.0030.001
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0830.012

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.

Opus teacher head0.029
GPT teacher head0.383
Teacher spread0.355 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2010
Admission routes1
Has abstractyes

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