Bibliographic record
Abstract
AIM: To study attitudes towards Rampton Hospital by reviewing the attitudes of external students and professionals in training following an arranged guided tour of the hospital; and examining media coverage of the hospital over one year. METHOD: All visitors had a guided day tour of Rampton. Everyone was given a questionnaire to complete at the end of the tour, and responses were reviewed. Rampton public relations department collects all print media coverage and monitors broadcasts in the UK. The department then assimilates this information into an annual report, which was examined for the relevant year. RESULTS: Questionnaires were given to 995 visitors and completed by 416 (42 per cent). Of those that returned the questionnaires, 95 per cent (n = 395) rated their satisfaction with the tour as either 'satisfied' or 'very satisfied'. A positive change in attitude was indicated by approximately one quarter of respondents (n = 105) following their tour. There were no negative changes in attitude expressed. Of the 203 press cuttings relating specifically to the hospital, 59 (29 per cent) were classed as positively enhancing and building the reputation of the hospital, 86 (42 per cent) were classed as negative and 58 (29 per cent) were classed as neutral. CONCLUSION: The tour of Rampton was valuable in bringing about a positive attitude change in the visitors. Although some media coverage assessed was negative, it had been expected to be more so. The authors wonder whether people's negative impressions are formed from the wider media, such as television dramas and movies.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".