Explorando potencialidades para la creación de una red de apoyo social a mujeres de habla portuguesa que viven con cáncer de mama en Toronto, Canadá
Bibliographic record
Abstract
Introduction: Health indicators tend to be altered due to the participation of people in social networks. Objective: To find out ideas of individuals belonging to Portuguese speaking communities in Toronto, Canada, about the possibility of creating a social support network for women experiencing breast cancer. Method: Nineteen participants of the present ethnographic and critical study answered to questions, providing their opinions regarding to the social support network and its positive and negative aspects. Also, the participants suggested other possible individuals who could participate and help in the creation of such network. Discussions were transcribed, analysed and coded using qualitative software called Atlas ti 6.0. Results: The main components for the creation of the social support network were: the demystification of breast cancer and its prevention, emphasis in health education, dissemination of the need of volunteers and a direct social support to those women. The positive aspects were the participation of oldest women as social leaders and the utilization of schools and religious institutions for publicity. Negative aspects that were perceived as barriers are: the belief that breast cancer is a disease lived by women, the lack of knowledge about its cure and rehabilitation, as well as a collective sensitiveness to it. Also, about the participation of community leaders, the suggestions were: diplomats, priests and pastors, schools directors and communication entrepreneurs. Conclusion: The creation of the social support network should consider the cultural sensitiveness and the inner diversity of the consulted Portuguese speaking communities. Due to the insufficient number of Angolan participants to sustain a major analysis, a special recommendation was that Angolan social leaders and professionals should be invited to design the structure of such network according to their specific cultural traits.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.026 | 0.013 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".