The Differences Between China & Canada in University Management and the Inspiration to China
Bibliographic record
Abstract
A comparative analysis of the Canadian university management mode is made,in which prominent characteristics of the Canadian university management model are found: the school-running mentality prominently stresses sense of industry,sense of market,and sense of cost accounting;the management strategy is rigorous——managing university affairs according to law,which makes sure that the uniersity can develop autonomically within the framework of the state's or the provincial laws and regulations;the running mode is flexible——public welfare,autonomy and internationalization,which makes sure that higher education fully opens to the society and the public and thus realizes the educational justice,fairness,openess,diversity and pluralism.Comparatively,over a hundred years of development of the Chinese universities and colleges,during which the university running mode has been throgh several time major readjustments,has steadily formed the university running mode of government administrating universities and educational administrationalization.Drawing the experience of the Canadian university management mode,it is suggested that in order to improve the Chinese university management or universities be given more self-governing powers of running a school;the university's status of a legal body be clarified;the reform of the managemental system inside colleges and universities be deepened;the university's administrative right and its academic right be balanced;the relationship between university and society be stressed;a multiple school running pattern be set up.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.008 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".