Supporting youth 12–24 during the COVID-19 pandemic: how Foundry is mobilizing to provide information, resources and hope across the province of British Columbia
Bibliographic record
Abstract
Foundry is a province-wide network of integrated health and social service centres for young people aged 12-24 in British Columbia (BC), Canada. Online resources and virtual care broaden Foundry's reach. Its online platform - foundrybc.ca - offers information and resources on topics such as mental health, sexual wellness, life skills, and other content suggested by youth and young adults. The COVID-19 pandemic has presented significant and unique challenges to the youth and their families/caregivers served by Foundry. Disruptions to school, access to essential healthcare services such as counselling, familial financial security and related consequences has left young people with heightened anxiety. The Foundry team mobilized to respond to these extenuating circumstances and support BC youth and their families/caregivers during this hard time through three goals: (1) to amplify (and translate for young people and their families/caregivers) key messages released by government to support public health responses to the COVID-19 pandemic; (2) to develop content that supports the needs of young people and their families/caregivers that existed before COVID-19 and are likely to be exacerbated as a result of this pandemic; and (3) to develop and host opportunities through social media and website articles to engage young people and their families/caregivers by creating a sense of community and promoting togetherness and social connection during the COVID-19 pandemic. Each goal and plan integrated the leadership, feedback and needs of youth and their families through engagement with Foundry's provincial youth and family advisory committees. Our study evaluated Foundry's media response to the COVID-19 pandemic by recording/measuring (1) the website/social content created, including emerged thematic topic areas; (2) the process of topic identification through engagement with youth and young adults; (3) the social and website analytics of the created content; and (4) the constant, critical team-reflection of our response to the pandemic. Following measurement and reflection, our team offers recommendations to health promotion organizations for future preparedness.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.036 | 0.006 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".