Educating the Next Generation of Remote Sensing Specialists: Skills and Industry Needs in a Changing World
Bibliographic record
Abstract
The landscape of post-secondary education has experienced a dramatic change in student outcomes over the past 20 years. The expectation for students in advanced education was a career in research and toward gaining employment in either academia or in government science. From our survey of university students and early career professionals, it was clear that there is an expectation gap between desired and probable post-secondary education outcomes. Our survey indicated that the majority of trainees, regardless of level of education, undervalue the importance of written and oral communication skills and overvalue specific methodological understanding relative to those employed in the field. While some of these dichotomies can be explained by the relative lack of experience of students, it also points to the nature of the foci of our training. While we are concerned with the production of the next leaders in remote sensing science, most will have careers that are different from their training. There is an opportunity to optimize the post-secondary education experience (student and faculty) with the inclusion of a broader view toward career outcomes.
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.
How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".