Bibliographic record
Abstract
BACKGROUND: Youth are often disenfranchised in their communities and may feel they have little voice. Since computers are an important aspect of youth culture, they may offer solutions to increasing youth participation in communities. OBJECTIVE: This qualitative case study investigated the perceptions of 19 (predominantly female) inner-city school youth about their use of computers and the Internet in a school-based community development project. METHODS: Youth working with public health nurses in a school-based community development project communicated with local community members using computer-mediated communication, surveyed peers online, built websites, searched for information online, and prepared project materials using computers and the Internet. Participant observation, semistructured interviews, analysis of online messages, and online- and paper-based surveys were used to gather data about youth's and adults' perceptions and use of the technologies. Constant comparison method and between-method triangulation were used in the analysis to satisfy the existence of themes. RESULTS: Not all youth were interested in working with computers. Some electronic messages from adults were perceived to be critical, and writing to adults was intimidating for some youth. In addition, technical problems were experienced. Despite these barriers, most youth perceived that using computers and the Internet reduced their anxiety concerning communication with adults, increased their control when dealing with adults, raised their perception of their social status, increased participation within the community, supported reflective thought, increased efficiency, and improved their access to resources. CONCLUSIONS: Overall, youth perceived computers and the Internet to be empowering tools, and they should be encouraged to use such technology to support them in community initiatives.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".