Citizen Science to ‘science with society’: an example from the Canadian Community Science Liaison programme
Bibliographic record
Abstract
This Canadian Community Science Liaison (CSL) programme (based at Mount Royal University in Calgary, Alberta) incorporates place- and curriculum-based Citizen Science projects into Kindergarten to Grade 12 classrooms. The first module created, the Geological Bumblebee Programme (GBBP), had >800 Grade 2-9 students build and install ~400 bumblebee boxes to monitor and learn about local bumblebee populations. In southern Alberta there are 23 Bumblebee species, with box occupation rates above 30%, and colonies ranging from a few individuals to over 200. One student stated that “I used to be scared of bumblebees, but now I recognize their importance for pollinating”. We now have ethics clearance to start a longitudinal study of the impacts of the GBBP on students, their families and their teachers.A new module on permafrost is now being trialled in Inuvik, Northwest Territories, in honour of the newly established International Union of Geological Sciences Geoheritage Site across the Mackenzie Delta Region. The permafrost module was co-created with a Grade 3 teacher, and Aurora Research Institute staff including the outreach coordinator, and two permafrost scientists. This participatory collaborative research starts with students doing some background research, then going into the field and collecting data, followed by evaluating and synthesising the data in the classroom. Activities include the use of geological and aerial maps, making their own pingo (ice cored hills), inputting data into applications such as Survey123 and the ‘good old fashioned’ measuring with a ruler.These place- and curriculum-based citizen science projects engage students while getting them out on the land, which is an important connection for the Indigenous communities across the Mackenzie Delta Region (Innuvialuit and Gwich’in in Inuvik). The data they collect will be used by scientists, while creating opportunities for schools to compare their results across permafrost regions, especially essential in a world with a changing climate. Schools in permafrost regions could also present their results to their southern counterparts to educate about permafrost and the impacts of climate change. This is particularly important in a country like Canada where 90% of the population lives within 300km of the southern border with the United States and most Canadians do not get the opportunity to visit the Northern Territories. One of the expected outcomes is for the students participating in this module to develop their own pride of place whilst illustrating the uniqueness of where they live.
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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.045 | 0.010 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.020 | 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".