Resource ReviewsGoVenture—Live the Life of an Entrepreneur. Sydney, Canada: MediaSpark Information Technology Solutions, 2000.The Business Disc: How to Start and Run a Small Business. Reisterstown, MD: Maryland Interactive Technologies, 2002.
Bibliographic record
Abstract
This article examines two computer-based decision-making experiences and exercises for teaching various business subjects, namely, GoVenture—Live the Life of an Entrepreneur, and The Business Disc: How to Start and Run a Small Business. The objective of GoVenture's designers was to have players experience the entrepreneur's work-a-day world. They have successfully done this by having the player, do all that is necessary to create a retail operation and then run it in simulated real time. Players must go through all the necessary clutter and busy work associated with starting a business, such as obtaining licenses and permits, filing the firm's name, obtaining its government identification number, signing up and making deposits for the business's utilities, and choosing the business and its location. The Business Disc, like the previous one, also has been designed to be an experiential learning and development simulation, but its approach is very different. It is basically a series of branched video clips that take the player through two phases associated with starting a new business. Phase I covers all the basic planning and major decisions that must be made by a start-up. The player meets Harrison Fields, an accountant who guides the participant through these decisions. Immersion in the exercise is very fast because Fields steers the player along the requisite path. Fields covers deciding whether the firm will be in the economy's retail, service, or manufacturing sector; the firm's name; the nature of business and its ownership structure; its location with the options of leasing or renting or owning the firm's property; hiring employees, writing their position descriptions, and setting their work schedules; determining the help's fringe benefits and withholding taxes; setting up all the records needed, and finally setting prices and creating sales estimates.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.189 | 0.097 |
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".