Great Britain Day Visits Survey, 2002-2003
Bibliographic record
Abstract
The main aim of the United Kingdom Day Visits Survey, the Great Britain Day Visits Survey (GBDVS), and latterly the England Leisure Visits Survey (ELVS), is to measure the extent of participation in day visits, and to estimate the scale and value of visits taken. In particular the principal investigators are interested in the extent of participation in different kinds of day trips, how frequently particular types of trip are undertaken, and associated expenditure. The survey also seeks to provide information on a number of other trip details, such as activities undertaken, areas visited, time spent at the main destination, modes of transport, distance travelled, number of people involved and the trip party composition. Respondents to the survey are generally asked to recall trips taken within the past two weeks. The 2002-2003 survey covered trips within Great Britain only, not Northern Ireland as had previously been the case, hence the change of name from United Kingdom Day Visits Survey to Great Britain Day Visits Survey. The survey also sought to provide estimates of leisure day visits to three main types of destination, including towns and cities, the countryside, and the seaside or coast. Within these types, trips involving visits to any of three further subsidiary destinations (woods and forests, and both navigable and non-navigable inland waters) could also be recorded.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.012 |
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".