Understanding the Hong Kong music curriculum through the lenses of posthumanism, postcolonialism, and poststructural psychoanalysis
Bibliographic record
Abstract
Abstract The use of “post‐isms” has become increasingly prominent in academic discourse because it offers new perspectives for gaining insight into current developments in human society and the historical dimension of culture. In the Hong Kong educational context, the concept of “post‐isms” has permeated the current music curriculum. The curriculum guide alludes to posthumanist primary interests, was created in the postcolonial state after the return of the sovereignty of Hong Kong from Britain to China in 1997, and is associated with poststructural psychoanalysis that values the subjectivity of listeners. This article investigates the entanglement of the Hong Kong music curriculum and the “post‐isms” from the perspectives of posthumanism, postcolonialism, and poststructural psychoanalysis. It is found that the curriculum guide demonstrates a commitment to ecology/human relations through both cross‐species communication and understanding, as well as pro‐nature humanism. It entangles with the concept of hybridity in postcolonialism and functions as a strategy of disavowal of the colonial legacy and the cultivation of the original national identity. The guide also perceives music as an agency that produces subjectivity by positioning the listener as subject. By investigating the Hong Kong music curriculum through the three lenses, implications for music curriculum development were drawn. It is urged that only when a music curriculum takes into account the multidimensionality of music can it reveal the greatest potential of music.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.017 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".