An Examination Of Decision Making On Social Media / Web 2.0 In A Health Promotion Tool For Population Based Violence Prevention
Bibliographic record
Abstract
Violence with its physical, emotional, and social, consequences has emerged and remain as one of the persistent problems facing humanity. The digital age presents us with a new social ecology in which collective engagement and action on the internet is influencing social discourse and norms. This represents a new opportunity for health promotion and violence prevention. This research, based in Canada, is an examination of decision making related to a social media/web 2.0 health promotion intervention for population-based violence prevention. This interdisciplinary mixed method study examined engagement with an online violence prevention- health promotion campaign the “Violence Prevention Charter” (VPC). It examined diffusion of the campaign within public sphere and a community of interest. Attention to adoption decisions and commitments as well as an exploration of the rationale for decision making was investigated within a bounded community. The study included five stages of inquiry: literature review, establishment of baseline diffusion metrics from the Violence Prevention Charter (VPC) web based campaign (quantitative), focus groups to understand generative mechanisms for participation in the online campaign, (qualitative), a social network analysis of a partner organization (Public Health Association of BC, Canada) to ascertain whether the aforementioned mechanisms were validated (quantitative) and finally application of the Bass Diffusion Model of Innovation to demonstrate adoption rates by the public and partner organization members. Modelling diffusion and adoption rates helped to ascertain the response to the campaign in the community of interest (quantitative). The application of Roger’s Diffusion of Innovation theory combined with a realist informed examination of context mechanism; and outcomes associated with the Violence Prevention Charter (VPC) and social network analysis (SNA) explained the process of online decision-making. The applied nature of the study reflected a pragmatic paradigm in which mixed methods helped to reveal and validate the mechanisms leading to engagement. Theories of health promotion and social norms provided varied lenses in examining the knowledge gathered from the study.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".