Combining Outreach and Cross-sectional Research to Gather Children’s Soil Values in Aotearoa New Zealand: Protocol for the Mixed Methods Soilsafe Kids Program
Bibliographic record
Abstract
BACKGROUND: Soil underpins most terrestrial systems; hence, its degradation should concern everyone. In 2021, Soilsafe Aotearoa surveyed the adult population of New Zealand about how they value soil, particularly values related to how they care about and are concerned about soil. Pursuant to this study, Soilsafe Kids (the outreach branch of Soilsafe Aotearoa) developed a combined research and outreach program to collect a supplemental data set of children's soil values, so both adults' and children's voices can be considered when understanding the implications of different practices and how to care for presently "uncared for" or neglected soils in the future. OBJECTIVE: The program not only asks primary school students about their soil values but also aims to teach them about soil from many disciplinary perspectives to enhance their understanding and awareness of soil, and, more broadly, for knowledge production. METHODS: Here we describe the research protocol used in this Soilsafe Kids program. This program uses surveys (in the form of worksheets), focus groups (introduced as group discussions), and art projects to learn what children think about soil in Tāmaki Makaurau Auckland. We have received ethics approval from the University of Auckland's Human Participants Ethics Committee (reference number 23556) on March 25, 2022, for 3 years. RESULTS: We have begun recruiting participants and delivering the Soilsafe Kids program in schools across Tāmaki Makaurau Auckland. Our data collection is ongoing with final student engagement in the first quarter of 2023. We expect to analyze data at the start of 2023 and to disseminate results later this year. CONCLUSIONS: Once this study is complete, we will disseminate the final results to the research community, stakeholders, and the local community through conference presentations, journal articles, hui (meetings), on our website, and in art exhibits. We note that although Tāmaki Makaurau Auckland is home to the majority of people living in Aotearoa New Zealand, the Auckland region only represents a small portion of Aotearoa New Zealand's land, and findings are not generalizable to Aotearoa New Zealand as a whole. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/43390.
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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 | 0.056 | 0.036 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.053 | 0.013 |
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".