Bibliographic record
Abstract
This article innovatively combines the analysis of both cultural and outdoor activities in Canada, activities that have been mostly studied separately until now. This study thus feeds into the debate between the distinction framework (focusing on the highbrow/lowbrow opposition) and the omnivorism thesis (distinguishing between omnivorous and univorous groups) in cultural sociology. From Latent Class Analysis (LCA), this study identifies five clusters, which differentiate people practicing either or both cultural and outdoor activities. The clusters are labelled as follow: "tele-univore," "digital indoor," "conventional indoor," "outdoor univore," and "omnivore." Binary logistic regressions reveal that education, age and rural/urban identity are the key factors in identifying who practices which activities. The findings are threefold. First, while confirming the omnivore theory, our results show that cultural capital matters more than economic capital in explaining who participates in which activities. Second, rural people tend to be slightly more engaged than urban people in consumptive and motorized outdoor activities and less in all cultural activities. Third, the shift to digitization and the increase in outdoor activities appears to have exacerbated the divide between older and younger generations.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.010 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".