Outreach within the Bristol ChemLabS CETL (Centre for Excellence in Teaching and Learning)
Bibliographic record
Abstract
This paper presents an overview of the Bristol ChemLabS project. In particular, it describes the development and impacts of the outreach project within Bristol ChemLabS, the UK’s Centre for Excellence in Teaching and Learning (CETL) in practical chemistry, and its continuation beyond the funded project. The major elements of working with both primary and secondary aged students, both within their schools and within the undergraduate teaching laboratories, are described together with aspects of the science teacher training. The teaching elements include school’s conferences, workshops within the School of Chemistry as part of the Open Laboratory Programme, summer schools and overseas work. Evidence is provided that demonstrates the impact of this programme on enhancing positive attitudes toward science and further education for the school students, as well as providing enhancing and embedding learning opportunities for school students and their teachers. The very positive impacts on the postgraduate chemistry students that work alongside the School Teacher Fellow (STF), a secondary school teacher working within the School of Chemistry, is discussed and the vital role played by these postgraduates and the STF to the overall success of the Outreach Programme. Generating a sustainable (financially and in terms of personnel) Outreach programme of the size of Bristol ChemLabS (beyond the lifetime of the CETL programme) is a unique aspect amongst UK CETLs and the mechanism used to achieve this is also discussed.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.075 | 0.009 |
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".