Computer and Internet usage by Canadian dentists.
Bibliographic record
Abstract
OBJECTIVES: To determine the frequency of computers in Canadian dental offices and to assess their use; to evaluate Internet access and use in Canadian dental offices; and to compare use of computers and the Internet by Canadian dentists, by the general public and by other dental groups. METHODS: An anonymous, self-administered survey of Canadian dentists was conducted by mail. A potential mailing list of 14,052 active Canadian dentists was compiled from the 2003 records of provincial regulatory bodies. For each province, 7.8% of the general dentists were randomly selected with the help of computer software. The surveys were mailed to this stratified random sample of 1,096 dentists. RESULTS: The response rate was 28%. Of the 312 respondents, 4 (1%) were in full-time academic positions, 15 (5%) were not practising, and 9 (3%) provided incomplete data. Therefore, 284 survey responses were available for descriptive analysis. Two hundred and fifty-seven (90%) of the respondents had a computer in their primary practice. Computers were used mainly for administrative tasks (accounting, bookkeeping and scheduling) rather than clinical tasks. Internet access was common (185/250 or 74%), and high-speed Internet access (93/250 or 37%) was increasingly common, judging from the results of previous studies on computer use. The main reasons given for not having in-office Internet access were security or privacy concerns and no reported need for or interest in the service. CONCLUSIONS: Computer use was high in this sample of Canadian dentists, but a small proportion of dental offices remained without computers. Canadian dentists" use of the Internet was greater than that of American dentists, private enterprise and the North American public in general.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".