Ecosystem services in postsecondary and professional education: an overview of programs and courses
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
Postsecondary and informal professional educational opportunities have increasingly become an important mode of supporting the understanding, dissemination, and application of ecosystem services (ES). The development of professional activities and group characteristics (e.g. a shared vocabulary, common objectives, dedication of time) together with teaching and education are instrumental for the institutionalization of new ideas, concepts, and disciplines in society. Integrating ES into postsecondary and professional education can help us to understand complex human-environment interactions and shape policy towards greater socio-ecological sustainability. This study analyzes the current status of ES-related programs and courses offered at the postsecondary and professional levels around the world. We collected data in English on these opportunities in mid-2020 using Internet searches, crowdsourcing techniques, and personal knowledge and discovered 20 degree-granting programs and 112 courses focused on or related to ES. Our analyses suggest that most ES education is uncoordinated and aimed at graduate students (master’s or doctorate level), but is also interdisciplinary with an emphasis on ES as a plural concept. We argue that the continued evolution and application of ES depends on the concept’s integration into postsecondary and professional education and that more attention should be paid to these modes of knowledge sharing and building. Our analysis adds to the current understanding of the available formal and informal opportunities for learning about ES and provides a lens by which we can envision new pathways for increasing the reach and effectiveness of ES education and training.
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 | 0.000 | 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