Bibliographic record
Abstract
This poster introduces my post-doctoral research project and continues my aim to understand young people’s relationship with nature through inter/transdisciplinary research. One of the key findings from my doctoral study was that the use of stories within outdoor learning can be an effective way to foster familiarity, comfort and connections. My ‘Playing with Words’ project will include auto/ethnographical writing: reflecting on my experiences has the specific purpose of enabling me to understand how this may impact on the way we work (in practice) and on the way, we conduct and present research. I plan to conduct two phases of primary research: first, at the European Institute for Outdoor Adventure Education and Experiential Learning (EOE) seminar in Plymouth to gain a European perspective. Secondly, in Alberta, Canada I aim to gain an international perspective through delivering and reflecting on a ‘playshop’ I have been invited to present at the International Play Association (IPA) conference. I will be conducting field work in Alberta, either side of the IPA conference, to explore public environmental education and education programmes. In late 2016, the Canadian Parks Council launched a new strategy to connect young people with Nature in Canada. Called ‘The Nature Playbook’ (Canadian Parks Council 2016), it utilises a story-based approach, with the aim of guiding and inspiring actions that all Canadians can take to connect a new generation with Nature. I want to see how this is used in practice, and if it is transferable to UK based initiatives. \n \nReferences \nCanadian Parks Council (2016) The Nature Playbook. URL: http://www.parks-parcs.ca/english/nature-playbook.php Last Viewed: 29/04/2017
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.043 | 0.014 |
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".