Serious Game Relationship Between Socio-Economic and Territorial Condition
Bibliographic record
Abstract
This research models a sustainable development through a serious game. The sustainable development system is influenced by internal factors and external factors. Internal factors consist of three sub-systems, namely: Culture, structure and technology. External factors consist of three sub-systems, namely: environment, economic actors and socio-cultural actors. The model in this research is agent-based involving three types of agents (firm, worker, and policy), internal variables, and external variables using a dynamic system. The behavior of each variable is observed using a dynamic system model. By providing initial values in internal factor variables and external factor variables, agent movement can provide information about the firm-size condition, the income of workers and the effect of policy on the development of companies and workers. Determination of initial data from internal factor variables and external factor variables aims to achieve a balance between supply and demand. In a certain phase, it will produce an optimal value, shown by supply and demand are at the same point. This condition needs to be maintained by adjusting all input variables so that supply and demand are in an optimal position.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".