Moving forward: Conceptualizing comfort in information sources for enthusiast cyclists
Bibliographic record
Abstract
Abstract This research aims to identify how the notion of comfort in the context of bicycling is conveyed in an American bicycling magazine and online forum. An iterative approach, comprising of a content analysis and linguistic discourse analysis aims to go beyond the generally‐accepted definition that focuses on vibrations, and identify the different concepts and typical situations relevant to study comfort for enthusiast cyclists. Are discussed the selection criteria for the magazine and online forum, the development of the coding protocol (including the final operational definition of each concepts) and the method for retrieving and analyzing online forum posts. A quantitative analysis, looking at the number of occurrences for each concept and theme, combined with a qualitative analysis of pronoun use, positive and negative descriptors, and opposing statements shows a complex link between the cyclist, the bicycle, and the environment. The behaviour of the bicycle, environmental factors, what the cyclists thinks and feels as well as the goal of the ride affect how comfort is conceptualized.
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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 | 0.012 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.014 | 0.020 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| 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".