Making the Tools to Do-It-Together: Open-source Compression Screw Manufacturing Case Study
Bibliographic record
Abstract
A remaining challenge to enable free and open-source hardware (FOSH) to catch up with now industry-dominant free and open-source software (FOSS) is identifying appropriate business models. In this article a new FOSH business model is discussed, specialty components for fabricators, using a case study of an open-source screw manufacturer business. The case study explores the economics of building a system that is meant to fabricate a specialty component for other businesses and prosumers working in the distributed recycling and additive manufacturing (DRAM) space. The component payback time is calculated under various scenarios, the sales necessary to provide an enticing income for a small business is quantified, and the point at which business expansion is necessary is determined. The results indicate that, to serve the burgeoning DRAM market, more than 1,000 small businesses could follow a Do-It-Together (DIT) approach of sharing FOSH designs while manufacturing and profiting locally. JEL Codes: L17, O36
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".