Facebook use among early-career veterinarians in Ontario, Canada (March to May 2010)
Bibliographic record
Abstract
OBJECTIVE: To explore the nature and content of information publicly posted to Facebook by early-career veterinarians. DESIGN: Cross-sectional descriptive study. Sample-352 early-career veterinarians. PROCEDURES: Publicly accessible Facebook profiles were searched online from March to May 2010 for profiles of early-career veterinarians (graduates from 2004 through 2009) registered with the College of Veterinarians of Ontario, Canada. The content of veterinarians' Facebook profiles was evaluated and then categorized as low, medium, or high exposure in terms of the information a veterinarian had publicly posted to Facebook. Through the use of content analysis, high-exposure profiles were further analyzed for publicly posted information that may have posed risks to an individual's or the profession's public image. RESULTS: Facebook profiles for 352 of 494 (71%) registered early-career veterinarians were located. One-quarter (25%) of profiles were categorized as low exposure (ie, high privacy), over half (54%) as medium exposure (i.e., medium privacy), and 21% as high exposure (i.e., low privacy). Content analysis of the high-exposure profiles identified publicly posted information that may pose risks to an individual's or the profession's reputation, including breaches of client confidentiality, evidence of substance abuse, and demeaning comments toward others. CONCLUSIONS AND CLINICAL RELEVANCE: Almost a quarter of veterinarians' Facebook profiles viewed in the present study contained publicly available content of a questionable nature that could pose a risk to the reputation of the individual, his or her practice, or the veterinary profession. The increased use of Facebook and all types of social media points to the need for raised awareness by veterinarians of all ages of how to manage one's personal and professional identities online to minimize reputation risks for individuals and their practices and to protect the reputation and integrity of the veterinary profession.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".