Effectual Thinking: A Systematic Approach for Teaching Entrepreneurship as Part of a Design and Manufacture Lab
Bibliographic record
Abstract
Mr Rajesh Ganithi started his career in engineering with a Diploma in Tool and Die Making from NTTF, India in 1995. In the next twenty years he has gathered enormous amount of experience and exposure while working in various companies in various capacities in various countries. He started his work with IRS Singapore Pte Ltd as mould maker for five years from 1995. He joined Meridian Automotive systems, Canada in 2001 as Tool and Die maker. In 2005 he joined ATS Automation Tooling Systems, Canada as Tooling Engineer. He joined Prolink Molds Canada in 2008 as Manufacturing Engineer. Training students in CNC applications was part of his work in the last few years in Canada. In 2012 he joined UAE University as Engineer in-charge of the CNC lab. The lab was completely rejuvenated by Rajesh and he plays an active
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".