Citizen science in K–12 school‐based learning settings
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Citizen science, or the public participation in scientific research, is a mechanism for student engagement, and co‐creation of knowledge in the scientific research process. Through participation in citizen science initiatives within school‐based learning environments, students can gain field experience, direct project scope, and contribute to broader research objectives while simultaneously achieving learning outcomes and fostering connections to their local communities. To capture the breadth and scope of existing citizen science initiatives applied in Kindergarten–Grade 12 schools, a systematic mapping exercise was undertaken to evaluate common themes related to the type of activities students participated in (i.e., the collection, transcription, categorization, and analysis of data), along with their level of participation in the citizen science initiatives (i.e., crowdsourcing, distributed intelligence, participatory science, and extreme citizen science). Of the 77 manuscripts extracted in the systematic map, nearly all (67/77) involved data collection, and a significant proportion of manuscripts captured a distributed intelligence level of participation (56/77).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.032 | 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 it