NCompass Live: Lessons Learned Establishing A Technology Makerspace
Bibliographic record
Abstract
The library is the intellectual crossroads of the university, a place where students come to research, explore, and discover. It was in this spirit that a new service - an Innovation Lab - was established during the Fall Quarter of 2015 in the John M. Pfau Library at California State University, San Bernardino. The Innovation Lab is a technology-focused "Makerspace" for students that encourages creativity and inquiry, facilitates cross-disciplinary collaboration, and promotes true innovation. The ability to work hands-on with emerging technologies and rapidly prototype solutions gives students greater understanding of real-world problems. The lab is open to all CSUSB students regardless of discipline, skill set, or background. In addition, the lab is a safe space where students can learn to persevere in the face of failure - a skill central to lifelong learning and success in the 21st century. Embarking on an innovative new service can be rife with pitfalls and obstacles. The presenter, former Head of Library Information Technology at CSU's Pfau Library, will share the logistics involved with planning, implementing and maintaining a makerspace. Technologies (3D scanning, printing, and modeling; CNC milling, Arduino, RaspberryPi), services (workshops, peer-to-peer tutoring), and policies will be discussed. He will also share mistakes as well as triumphs, and will address the lessons learned during the first year of operation. Presenter: Jonathan Smith, Director for Library Technology, Sonoma (Calif.) State University.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.222 | 0.014 |
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; both teacher heads agree on what is shown here.
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".