How can we enable school students to learn and participate in science engagement initiatives? Roles and tasks of enablers
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
Involving school students in authentic research beyond their school learning means creating participatory, out-of-school opportunities related to research processes, giving them a voice in the applied format of science engagement. Important for such endeavours is a group of people we identify as “enablers”. Based on insights from two long-term and large-scale science engagement initiatives in Germany (the Darwin Day science outreach and the Plastic Pirates citizen science program), we identified four principal work tasks of enablers. They are described as (i) aligning the needs, expectations and goals of involved participants, (ii) translating differing conceptions about science into shared visions, (iii) guiding the design of the initiative through educational theory, and (iv) evaluating the success of the out-of-school science engagement initiative. We further suggest that self-awareness of being an enabler, working at the interface of the research and education sphere, is an important prerequisite to successfully collaborate with participants.
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) | 0.000 | 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