The Grand Entrance: A Faculty and Staff Housing Development
Bibliographic record
Abstract
The team chose this project because it is one of many upcoming projects detailed for California Polytechnic State University (University) in the 2035 Master plan. The University has a capacity of over 21,000 students and 3,000 employees, including 1,400 faculty. Many students and faculty from the University live within city limits, with students making up a majority of the rental market in the city. In a typical four-bedroom house, four students with four separate incomes can rent out a house together and pay a much higher rent than a faculty member with one to two incomes could. Additionally, The City of San Luis Obispo has reached a near-zero vacancy rate, with the average rent passing the average salary of a new University employee. As a result of this, many faculty members are forced to look for housing in the cities surround San Luis Obispo, creating longer and more inconvenient commutes. The University is aware of increasing difficulties for faculty to reside in the area and is seeking a design proposal for a faculty housing development on the corner of Slack St and Grand Ave. The Request for Proposals (RFP), issued in June 2022, outlined the need for 150-220 new rental and for sale units, with a variety of unit types and floor plans. This report serves as the deliverable for the University’s RFP, consisting of Site Analysis, Visioning, and Final Design. Over the course of Spring Quarter 2023, the team conducted several research methods, including in person site visits, existing building tours, and data collection from various news sources. We compiled this information into the first chapter of this report: SIte Context and Analysis. This chapter is organized into different types of data: Physical, Social, Regulatory, Cultural & Historical, and University. All data was summarized into the Strengths, Weaknesses, Opportunities, and Threats (SWOT) table and the Site Analysis Map. Next, the team took all the Site Analysis data and used it to create a vision for the project. We began by establishing design principals to guide our inspiration for the project. Once principals were established, the team conducted case studies based on housing projects in San Luis Obispo as well as other Universities. Pulling inspiration from these studies, we developed Goals, Principals, and Design Ideas for our project. Keeping these goals in mind, we began the design phase with two preliminary concept diagrams and final concept for the project. In the final few weeks of Spring Quarter, we began the Design Phase. Using SketchUp, Illustrator, and Photoshop, the team developed an illustrative site plan, a 3D model, and two perspective views of our final site. The Design chapter includes these deliverables as well as a project description and development table that connects our final design to the University’s RFP.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.055 | 0.010 |
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".