Bibliographic record
Abstract
Within a quarter century after the end of World War II (1945-1970), largely because of the support and investment it received from the State, the University of California had changed from two modest-size general campuses (Berkeley and Los Angeles) and the medical campus in San Francisco (UCSF), to a system of eight general campuses. California was at the pinnacle of its success-its economy strong and growing. Since then, however, the fiscal and political problems facing California have led to a steady erosion in funding support for the University of California, and now are leading to a debate regarding its future. If UC has in the past been an engine propelling the growth of California's economy, it would appear to be wise policy to place a high priority on repairing the damage which has been done to it, and will weaken its ability to serve students and the people of the State and nation. While most observers acknowledge that this is a desired goal, there is little agreement on how best to achieve it. Setting aside the limited numbers who would opt for the status quo, this paper discusses three scenarios for UC. The first is a return to the status quo ante; the second is a full move toward privatization; and the third is a hybrid approach. This last option would mean retaining some of the elements of the past partnership between the state and the university, and could be implemented without unrealistic costs to the State or UC, and allow for the continuing academic health of the university. This last option could be exercised by UC as a whole, by several of the campuses operating through UC, or by several campuses (presumably the same ones as discussed under the "privatization" option) becoming quasi-independent of the current system. It could even be exercised, with the approval of campus and UC officials, by schools, colleges or other intra-campus organizations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".