Responses to fiscal constraints: the use of planning and budget techniques at two Ontario colleges and two Ontario universities
Bibliographic record
Abstract
This thesis compares a community college and a university in each of two separate Ontario jurisdictions to determine if, in response to operational impacts and Provincial funding constraints since the early 1990s, planning and budgeting approaches have changed and whether or not the changes were different for different institutions. Interviews occurred in late 2004 and the first half of 2005. It was found that planning and budget approaches have changed due to funding constraints. The majority of those interviewed saw their institution moving from Incremental and Advocacy approaches to Strategic and (to a lesser extent) Rational Planning approaches. Institutional budget cuts have not always been across the board (ATB). Differential approaches tended to occur in the 1990s, when the provincial funding cuts studied in this thesis began, but they were replaced with broad common-percentage approaches once perceived areas of surplus were exhausted. In some instances during this decade, a "reverse differential" approach was applied. For example, the provost from an institution hears from divisions that they believe they are being hit heavily by ATB cuts. He uses central funds to assist divisions case by case. As for fiscal responses and other strategies to cope with funding cuts, revenues from non-Operating-Budget activities have become more important. New markets for educational programs have been sought and traditional markets have been mined more fully. In general, class sizes have increased, grading approaches have become simpler, and part-time instruction more common. Although reduced government funding might lead to reduced attention to performance budgeting, this has not been the case. Interviewees in senior administrative positions at all institutions perceived greater accountability and reduced autonomy. The fact that revenue from the Key Performance Indicator provincial grant is a larger component of overall funding for Ontario colleges compared with universities (colleges report on more indicators) supported an increase in performance tracking by the colleges.
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 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 | 0.008 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.020 | 0.005 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".