SATELLITES: Students and Teachers Exploring Local Landscapes to Interpret the Earth from Space
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
SATELLITES program is designed to introduce in-service teachers and K-12 students to basic geographic concepts, geospatial technology (e.g., remote sensing, GIS, GPS, and digital elevation modeling), related data, and applications in complex concepts in Earth System Science. Teachers, who received extensive SATELLITES training in a one-week summer institute in 2006, integrated concepts and technologies in their school curriculum the following fall by engaging students in inquiry-based research projects during an intensive field campaign. 151 K-12 teachers from 110 schools have received SATELLITES training over the last three years and over 10,000 students representing more than 300 schools from every state in the United States and several other countries including Canada, Australia, Great Britain and China have participated in data collection during field campaigns. In 2006, 1200 student observations were recorded and 600 students attended the 2006 annual conference where 60 inquiry-based research project posters were presented. After participation in SATELLITES, teachers' content knowledge in geotechnologies and related sciences increased significantly. Teacher's reported an increase in perceptions of their ability to do inquiry science and employ inquiry-based instruction. They also reported a significant increase in student engagement when students collected data and worked through the scientific process while participating in SATELLITES inquiry projects.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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