Bibliographic record
Abstract
A DETAILED DESCRIPTION OF THE RECOMMENDED CHANGE (Attach additional pages if space is not sufficient.)1) It is recommended to cancel MFIN 603 and to revise MFIN 602 so as to incorporate topics on both microeconomics and macroeconomics.Topics on macroeconomics were originally covered in MFIN 603.In doing so, we streamline the content and focus on the core material that directly caters for the needs of the understanding of economic concepts within a finance curriculum.A new required course MFIN 605 (Financial Instruments and Their Markets) is created to provide students with a practical understanding of various financial instruments and their markets.The requests for revising MFIN 602, cancelling MFIN 603, and creating the new MFIN 605 are being submitted concurrently but separately.The curriculum after this change will consist of the same number of required courses.2) It is recommended to expand the selected elective list to include four other MBA courses: F724 (Venture Capital and Private Equity), F725 (Personal Financial Management), F741 (Introduction to FinTech), and F743 (Big Data in Finance).3) It is recommended to change the description to: "Electives courses will be from a selected list of finance electives presently offered in the MBA program or, with the approval of the Program Director and consent of the department involved, electives in business, mathematics, statistics or economics."4) It is recommended to explicitly state in the description of the program in the Graduate calendar that not all the elective courses on the selected list may be offered in a given academic term.5) It is recommended to include the participation in a video interview as an additional admission requirement.Please see the details of these changes in the attached Appendix 1. RATIONALE FOR THE RECOMMENDED CHANGE (How does the requirement fit into the department's program and/or tie to existing Program Learning Outcomes from the program's IQAP cyclical review?):Please see the rationale for the changes in the attached Appendix 1.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.772 | 0.700 |
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; the direct Gemma label and the distilled Codex classifier 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".