Bibliographic record
Abstract
Canada is an important player in the international furniture industry. It is a big and open market and a large producer, although slow growing. CSIL ranks the country as the 9th largest furniture producer and consumer at world level. In recent years the rapid growth of imports and the decline in exports have turned Canada into a net importer of furniture. Nevertheless Canada remains among the top ten exporters of furniture worldwide. This research is part of the Country Furniture Outlook Series, covering at present 70 countries. Each Country Furniture Outlook Report is structured as follows: Furniture sector performance is analyzed through updated furniture statistics and through tables, graphs and maps. Information covers all the main variables necessary to analyze the sector, from the supply side (Productive Factors, Furniture Production) to the market side (Demand Determinants, Furniture Consumption), also considering the international trading activity (Furniture Imports and Furniture Exports). Future sector prospects and CSIL's assessment of market potential are also provided (Furniture Market Potential) and cross-country comparison is also shown in order to enrich the analysis (Country Rankings). Short profiles of manufacturers and distributors operating in the country and a list of international Furniture Fairs, Furniture Association and Professional Furniture magazines are also provided. Background country information is also provided through summarized detailed statistics (Socio-Economic Data) as well as the country's attractiveness in terms of economic competitiveness (Business Climate).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.137 | 0.047 |
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".