Clean air together Dublin: impact on air quality awareness, attitudes and behaviour
Bibliographic record
Abstract
Clean Air Together (CAT) is a citizen science project where people voluntarily sign up to measure levels of nitrogen dioxide (NO2) pollution in their local area. In this study, we assessed the impact of CAT on awareness, attitudes and behaviours of participants in relation to air quality. Selected participants (and those who signed up for the study but who were ultimately not selected to engage in NO2 measurement, referred to in this report as non-selected participants) were invited to complete three surveys at various points in 2021 and 2022. It is these survey responses that are used to evaluate the impact of CAT participation on awareness, attitudes and behaviour in relation to air quality. While the analysis was hindered by small samples, the research identified a number of key findings: Compared to the general Dublin population aged 18+, CAT participants were more concentrated in the middle age groups (aged 35-64), and nearly half had postgraduate-level educational qualifications. The baseline survey was conducted in September 2021, at the start of the CAT project and before participants participated in NO2 measurement or received infographics and further information on NO2. It revealed that CAT participants were more aware of NO2 (and other environmental risks) than the general Dublin population aged 18+, and more likely to correctly identify the main source of NO2 pollution. However, nearly one-quarter of CAT participants did not know the most significant source of NO2 pollution, and a further quarter answered this question incorrectly. In terms of attitudes, CAT participants were, in general, more supportive of various policy measures to reduce air pollution than the overall Dublin population aged 18+. Analysis of CAT participants who responded to the first (September 2021) and second (March 2022) surveys showed that awareness of NO2-related issues improved. For example, the proportion who correctly identified the most significant source of NO2 increased from just over 50 per cent to nearly 70 per cent, with an additional large decline in the proportion of participants who reported that they did not know the most significant source of NO2 pollution.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".