Community in the Making: Exploring opportunities to enhance the Canadian makerspace ecosystem
Bibliographic record
Abstract
Although makerspaces present opportunities to enhance community wellbeing and social innovation, the potential of the Canadian makerspace ecosystem has yet to be realized. In combining tools and methods from the fields of design thinking, systems thinking, and business strategy, this research reveals insights and identifies opportunities towards strengthening Canada’s makerspace ecosystem. \n \nCommunity in the Making follows a three step methodology: Part 1 – Framing, Part 2 – Situating, and Part 3 – Learning. Part 1 begins by exploring the concept of makerspaces, their history, and their context within Canada’s social economy, through background research and a literature review. Part 2 then provides an overview of the makerspace climate in Canada, based on a research questionnaire, with a focus on existing makerspace attributes, structures, and business models. Lastly, Part 3 presents nine themes, and corresponding opportunities, developed from interviews and site visits, which suggest ways to enhance makerspace viability and elevate makerspace impact across Canada. These themes include: \n \n- \tMeasuring Magic: Converting Meaning(fulness) in Makerspaces; \n- \tThe Pursuit of Creativity; \n- Placed-based Spaces; \n- Third (maker)Space; \n- \tLocked Out: Rentals and Real Estate; \n- \t“Vibes” Are Everything; \n- \tThe Power of Partnerships; \n- \tThe Internal Economy; and \n- \tRemoving Barriers to Access. \n \nThe project concludes with the finding that makerspaces are far more than places to make; they are hubs for social innovation and creativity, and most importantly, vibrant communities integral to Canada’s creative ecosystem. \n \nThe hope is that this work will spark conversations and promote collaboration across Canada’s maker community, in an effort towards building a thriving makerspace ecosystem.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.000 | 0.005 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".