To What Extent Educational Planning and Policy Decision ought to Be Guided by Economic Considerations – A Case Study on Recent Educational Developments of Hong Kong
Bibliographic record
Abstract
The ascendance to popularity of the liberal ideologies and the concepts of political economy of education will be put forward as the root cause for an increasing subordination of education objectives to national economic goals. Through a case study of the educational development of Hong Kong, this paper will evaluate the extent to which educational planning and policy decision should be guided by economic considerations. Although the rapid economic growth of Hong Kong and the rapid expansion of its education system in the past decades took place in parallel, there is no evidence that Hong Kong’s economic success is directly brought about by its education. It will be concluded that apart from economic contributions, education has its own intrinsic values. While economic considerations are useful for planning and policymaking at a macro level, it may not be appropriate to indiscriminately apply economic principles in an intrusive way to direct the priorities of institution management and classroom teaching.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".