Tech-social synergy: nurturing community well-being
Bibliographic record
Abstract
Dear editors, Strup et al., in a recent article, found that the pandemic has raised awareness of the importance and potential benefits of community-based networks for public health. Community social capital in promoting engagement, resilience and well-being is crucial.1 We complement these findings, that in the pursuit of community well-being, concocting the integration of social capital and technology is a harmonious formula. In a modern era characterized by technological transformation and increasingly complex social dynamics, the combination of technology and social capital is essential in shaping community welfare. Physically and mentally well communities are formed through a combination of factors, such as an effective health system, strong social support and public awareness of the importance of well-being.2 Easy access to physical and mental health services is a key feature.3 These communities are able to create a balance between the demands of work and personal life while providing individuals with support and empowerment. To achieve this, technology integration strategies and social capital that support effectiveness and accessibility are required. Technology and social capital play a central role in optimizing people's physical health. Technology, bringing solutions such as telemedicine4 and wearable devices, facilitates wider access to health services, monitoring of physical conditions and dissemination of health information.5 On the other hand, social capital, such as social support and community engagement, forms the basis for the promotion of healthy lifestyles,6 collaboration in physical activities and acceptance of positive health-related norms. The synergy between technology and social capital creates a favourable environment for concerted efforts to holistically improve people's physical health. The role of technology and social capital in optimizing people's mental health is significant. Technology, through mental health apps such as the use of the metaverse,7 online counselling platforms8 and other digital resources, provides easy9 and anonymous access to psychological support to even the elderly.10 Meanwhile, social capital, such as social support from family and friends, and participation in community activities play a key role in reducing stigma, raising awareness and creating a supportive environment for mental health.11 The synergy between technology and social capital creates an effective channel to support people's mental health in a holistic and inclusive way. The implementation of community welfare through the synergy of technology and social capital requires training and education of communities in technology skills and social capital enhancement. It is necessary to provide an equitable access to technology and build local digital platforms, including digital infrastructure in less developed areas. Online health and education services are also introduced to improve the accessibility. Local governments need to develop policies that support technological development and social capital strengthening. Health and education institutions are responsible for providing accessible services and education through technology. Technology developers play a role in developing and implementing appropriate technological solutions. Local communities are expected to actively participate, identify needs and build social capital. Non-governmental organizations, businesses, universities, media and local civic institutions also have a responsibility to support, disseminate information and ensure the sustainability of community welfare programmes. The involvement of all these stakeholders is key to creating holistic and sustainable solutions. We have no conflicts of interest to disclose. The authors declared that no funding was received for this paper. The authors stated that there is no conflict of interest regarding the subject matter or material discussed and confirmed the data available in this manuscript's article.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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".