Creating a climate changed future with the sea level rise interactive-fiction game “Lagos2199”
Bibliographic record
Abstract
Story-based futures serve an important role in climate change scenario development. Stories are particularly useful in exploring sea level rise possibilities, since we know many coastal areas are specifically vulnerable to accelerating rises in sea level. This discrete change in coastline is different from most other climate change impacts, and offers a clear basis for scientifically informed, future scenarios. We demonstrated this with a creative world-building effort set in Lagos, Nigeria in the year 2199. Further, we employed story-based scenario development, and created a learning-oriented serious game that allows users to experience a future Lagos in an open-ended, text-based adventure style. This collaborative process blended scientific research, story-telling, and artistic co-creation to iteratively construct the game “Lagos2199”. A pilot-use case of Lagos2199 is documented herein, with preliminary survey results from the student users. We present two core insights. First, we demonstrate how scientific projections regarding sea level rise can be leveraged as an entry point for world-building and scenario development of the future. Second, we show that such a scenario can be transformed into an immersive, story-based serious game to creatively communicate possible futures. Providing the next generation of citizens with fluency in both climate change impacts and how society will interact with such impacts is critical for providing adaptive capacity over the coming decades and centuries of accelerating global change.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".