Bibliographic record
Abstract
From its inception, Grand Beach, Manitoba, quickly became one of Western Canada’s foremost recreational, cottage resort localities and it has regained that position despite many years of neglect and abuse. Dominion government surveyors were the first to recognize the recreational possibilities of the beach, but this potential was not realized until the Canadian Northern Railway extended a line up the eastern side of Lake Winnipeg. Under a leasing arrangement with the provincial government, the railway company developed Grand Beach peninsula into an extremely popular lakeside resort and camping area, which during its heyday, was visited by countless thousands of excursionists and longer-term vacationers. This paper focuses on the development of the ‘Campsite’, an area initially created for temporary summer campers, but which was soon converted to leasehold lots available for long-term cottage development. Although the area is now part of Grand Beach Provincial Park, the cottages built in the old campground still remain. However, they are now being progressively upgraded, converted into more permanent fixtures, and many adapted for year-round use. Surveys of cottagers identify some interesting ownership patterns and reveal the strength of attachment that many of the predominantly urban residents have for their cottages or second homes, as they are commonly referred to in the academic literature.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.031 | 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".