Report for Ulster Wildlife: An evaluation of the Grassroots Challenge Project 2019-20
Bibliographic record
Abstract
This report presents findings from an evaluation of Ulster Wildlife’s Grassroots Challenge Project, together with young people’s views, opinions and concerns about environmental issues and actions, which will be used to inform future work. The Grassroots Challenge project has been running since 2015 and this evaluation presents evidence from activities conducted between September 2019 and March 2020. The Grassroots Challenge gives young people aged 11 – 24 the opportunity to gain essential skills, knowledge and training to take action for wildlife in their local area, whilst also improving their confidence, employability and well-being. The overall aim of the project is to link with established structures and groups to offer opportunities for young people to develop skills and knowledge and to design and deliver environmental projects that will enhance their local area and engage their communities in environmental action. This report presents evidence that the Grassroots Challenge Project benefits the young people involved across all the evaluation statements, which represent the aims of the project. During the focus groups the majority of young people said they want to make a difference for nature but cited a lack of opportunities and/or the promotion of existing ones as a major issue. Many of the young people also explained that there should be more opportunities, publicised using a greater variety of mediums.
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 | 0.078 | 0.074 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".