Hong Kong’s New Creative Industries: The Example of the Video Games Sector
Bibliographic record
Abstract
Hong Kong has considerable creative and entrepreneurial resources, and the opportunity to build a vibrant set of creative industries, including in the new sectors such as video games, animation, and computer graphics. However, as it stands, some of these industries, especially that of the games industry, are fledgling in nature. Strong supporting institutions already exist, but it is essential to discover how industry can be better supported with existing and new resources — financial and otherwise. The opportunities are immense, but so is the competition. The new entertainment media sectors are growing at a faster pace than most economic sectors in many countries. At the same time, the expected global markets for new creative industries (especially games and animation) are considered to be huge.1 India’s NASSCOM estimated the global market for animation to be approaching US$50 billion, while one consultancy, DFC Intelligence, reported that the total global games market (including PC, online, and console) would rise from US$33 billion in 2007 to US$57 billion by 2009.2 At the same time, investments in virtual worlds, including associated technologies and social networking sites, in the US alone have been in the few hundred million dollars range per quarter over 2007.3
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".