Exploring the Purchasing Experience of Cross-Cultural Consumers in Northern Remote, Rural Communities: Thompson, Manitoba
Bibliographic record
Abstract
Thompson is the largest community in northern Manitoba which was built originally to service the mining industry. This community has faced challenges in providing effective customer service and sufficient goods to meet local demands. Like many other resource based communities in northern Canada, the human resource base includes transitory workers, a large First Nations and Metis population and in recent years an increasing immigrant and temporary foreign worker population. As a service centre for northern Manitoba, it is critical to maintain a robust retail and service sector which meets the purchasing needs of the community. This research explores some of the nuances of purchasing patterns through primary and retail service sector gaps, experience of residents with customer service, and the role of various cultural groups and variations in purchasing experiences. Our findings indicate that there were low levels of customer satisfaction and there was a need for cross cultural customer service. Respondents also indicated that the limited availability of products and services in the community resulted in retail leakage. While the economic livelihood of this community is not solely tied to resource extractive industries such as mining, the link is significant enough to merit significant vision by local leadership to ensure that the economy is diverse and responsive to the economic, social and cultural climate of the region.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".