Bibliographic record
Abstract
Be at the forefront of climate change decision making! Yukon College—Yukon University from May 2020—offers a unique ten-month, part-time, post-degree Certificate in Climate Change Policy (CCPC). The graduate-level program was launched in Fall 2017, and it is delivered online with an experiential component.The CCPC is designed for mid-career professionals, graduate students, and/or policy practitioners, and is accessible to students from diverse disciplinary backgrounds. In four courses and a field school, students explore science, policy, and Indigenous world views to understand the causes, economics, and impacts of climate change, and to learn how to shape contemporary climate change policy. Main topics include climate change science, climate change adaptation and mitigation, policy process, Indigenous world views, governance, strategic planning, leadership, communication, education, and Yukon First Nations core competency.Students benefit from the experience of multiple guest speakers who are professionals in this interdisciplinary field (see below for biographies of all 2019-2020 lecturers). Instruction is asynchronous, by online lecture, but also includes a weekly online discussion forum, self-directed and team assignments, and readings. The in-person field school takes place in the Yukon and runs for two weeks in an excursion-style format—visiting specific sites and connecting with communities to illustrate climate change and related policy needs and initiatives in the North. Without aiming to complete the certificate, students can take up to two courses individually. This option excludes the field school component..... ..... continued
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".