Designing and Implementing an Information System for the Dental Office of Branckowitz & Young
Bibliographic record
Abstract
ABSTRACT This case provides students with the opportunity to create a functional information system (IS) for a service company. The case facilitates a guided hands‐on experience where students learn to analyze a business entity in the context of its environment; recognize what business processes comprise an entity's value chain; and develop, document, and implement a tailor‐made IS to support the entity's operation. In order to keep the amount of development realistic and the system transparent for students, the case focuses on a small service company: a dental office. The case uses a resource—events—agents (REA) analytical framework for modeling and Microsoft Access for IS implementation. The case is structured modularly, enabling instructors to either explain material or demonstrate analysis/development of a segment of an IS in class and then challenge the students to complete the module's development following the instructor's example. Instructors have the flexibility to give students fewer (or additional) directions in developing the information system, depending on the students' backgrounds and abilities. Instructors also have a choice to limit the scope of the development and implementation to any number of four business processes.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".