Critical making with a raspberry pi ‐ towards a conceptualization of librarians as makers
Bibliographic record
Abstract
ABSTRACT Makerspaces, designated spaces to foster creativity and technology skills, are increasingly being incorporated into libraries. Although makerspaces in libraries are depicted positively in the literature and are praised by professional organizations, there is little exploration of the acculturation that results as libraries and makerspaces learn to coexist. In keeping with Matt Ratto's model of “critical making,” we used the process of collaboratively building an interactive Readers’ Advisory Device (RAD) that runs on a Raspberry Pi computer to elicit introspection. In this poster we describe how our interdisciplinary group faced challenges working with unfamiliar tools and technology through a non‐hierarchical, collaborative, and iterative process, seeking knowledge and skills from the maker community. We then engaged the wider community around both how and why we developed this device by exhibiting it at a Maker Faire. Our experience taught us about the making process and helped us think critically about the intersection of libraries and makerspace cultural values. We found that making is as much an act of networking as of creation.
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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 | 0.011 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.011 | 0.045 |
| Scholarly communication | 0.020 | 0.017 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".