Features of the Formation and Development of the Video Game Industry in Japan in the Last Quarter of the XX-XXI Centuries
Bibliographic record
Abstract
The specifics of the historical development of the Japanese gaming industry are considered. A periodization of the history of the gaming industry in Japan is proposed, a description of its main stages is presented: the emergence in the 1970s, access to foreign markets in the 1980s, stagnation and crisis of the 1990-2000s, the global triumph of the 2010s. It is proved that it was accelerated economic development and a high standard of living that allowed Japan to switch to the consumption of such a product as video games. The complex of historical, economic and sociocultural factors that provided Japanese companies with competitive advantages in the global video game market was identified and analyzed. Particular attention is paid to the impact of information and communication technologies on these processes. The role of the American factor in the formation and development of the gaming industry in Japan, as well as in the promotion of Japanese gaming products to foreign markets is disclosed. The constructive potential of the Japanese practice of intersectoral cooperation of game industry companies with large industrial giants and with representatives of the art sphere is shown. It is noted that the involvement in the gaming industry of highly qualified specialists from the entertainment industry (anime and manga) allowed shifting the emphasis from the technological aspects of video games to their content, genre diversity and plot content. The authors come to the conclusion that the historical experience of the gaming industry in Japan indicates the significant role of this industry in the economic and social development of modern states.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".