Evaluation of a national citizen science programme for public benefit: Engagement in the citizen science of Soilsafe Aotearoa
Notice bibliographique
Résumé
Aotearoa New Zealand’s history of soil contamination combined with its culture of home gardening has the potential to put New Zealanders at risk of exposure to trace metal contaminants from their backyards. Soilsafe Aotearoa (SSA) is a New Zealand-based citizen science (CS) programme that examines this risk, screening for concentrations of trace contaminants in participants’ domestic soils. CS programmes generally promise to make science more democratic by narrowing the gap between science and the public; SSA does this by returning heavy metals report of each participant’s soil screening back to them along with interpretive data and guidance of what to do next. \nThis thesis explores how participants engaged with this citizen science programme and the impact of their engagement by looking at the demographics of the citizen scientists, their motivations for engagement, and the outcomes of their engagement. Data was collected through an online survey sent out to previous SSA participants who had their soils screened and had received their results (n=855 at that time). Respondents (n=161) were mainly women of European descent who had received at least an undergraduate degree, who were part of wealthier households, and who owned their homes. Motivations for engagement typically revolved around their concerns for the safety of garden food production. Respondents felt that the biggest gains in knowledge from participating were in learning about their own soils from the results they had received from SSA, though only about a quarter of respondents took action to remediate any issues, such as through soil remediation, changing the plants growing in their garden, or learning more about the problem and potential solutions. Factors such as cost, feasibility, pre-existing knowledge, and level of risk determined the actions that respondents did or did not take. A large majority of respondents found SSA’s free soil metal screening service to be useful and would recommend it to others. Recommended further research directions include engaging with underrepresented groups (e.g., Māori, Pasifika, youth, renters) and exploring more deeply the soil values of participants through methods such as interviews or focus group discussions.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,017 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».