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Record W4392581568 · doi:10.5194/egusphere-egu24-12424

Climate Tick-Tock: sparking climate action through a cooperative and educational game on climate change in the 21st century

2024· preprint· en· W4392581568 on OpenAlexaboutno aff
François Dulac

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicEarth Systems and Cosmic Evolution
Canadian institutionsnot available
Fundersnot available
KeywordsClimate changeAction (physics)Natural resource economicsGeographyEnvironmental resource managementEcologyEnvironmental scienceEconomicsBiologyPhysics

Abstract

fetched live from OpenAlex

Feeling the need for an interactive tool to make the human-induced climate change more tangible to the broad public, climate scientists from LSCE proposed to develop an educative game to raise middle and high school student awareness. A serious and educational, cooperative board game for up to 5 players, named ClimaTicTac (https://climatictac.ipsl.fr), has been created at IPSL with the help of ASTS, a scientific outreach association. This presentation describes the game mechanics and diffusion strategy.The game is adapted to all players with good reading and abstraction capabilities (≈10+ years). It simulates essential processes related to climate change and associated impacts, mitigation, and adaptation. It is based on a world map including 30 cities vulnerable to climate change, which may become uninhabitable following damage accumulation, a timescale showing the rounds of play throughout the century, and a CO2 atmospheric concentration scale. Randomly drawn cards describe initial scenarios, and hazards and possible positive actions affecting CO2 emissions and three categories of damages to cities (on health, food, or infrastructures). To win the game, players must reach a double objective, with thresholds depending on the game difficulty level, on atmospheric CO2 concentration to limit global warming and on the number of cities rendered unliveable. Optional fun challenges (drawing, mime, word-of-mouth) are randomly proposed to counteract eco-anxiety. Rules have been designed to help players feel the climate change impact at both global and local levels, and realize the importance of early reduction of CO2 emissions, of collaboration for optimizing action strategies, and of inequalities in exposure to impacts. The game fully relies on current knowledge and realistic events, and the project team has been awarded the CNRS medal for scientific outreach.The game has first been distributed by local authorities for open-licence use in middle schools. Science animators can carry game sessions for teenagers and adults, followed by discussions on climate change. Middle and high school teachers may also be trained. The game content has been translated into Catalan, English, Portuguese and Spanish (new translations welcome), and is available for self-printing and non-commercial use.Following success towards a variety of public, the board game has been slightly adapted as a family game by Bioviva Editions for distribution in France, Belgium, Switzerland and Canada under the name Climat Tic-Tac (https://www.bioviva.com/fr/bioviva-famille/169-362-climat-tic-tac.html), including a semi-cooperative game option with lobbies. In addition, Climat Tic-Tac has been adapted by the association Games for Citizens as an electronic game available online on the Ikigai video game platform (https://ikigai.games/games/gameDetails/105). Challenges consist in quiz, gap-fill or timeline questions. Several connected players can share a game but a single player can simulate several players. Additional university-level educational content will be linked and an English video version named Climate-Tick-Tock is planned.Finally, a multidisciplinary research project (EVABIO) is underway involving high school teenagers to investigate the impacts of play sessions. Integrating social psychology and experimental economics, it aims to analyze changes in explicit and implicit attitudes, transformations in social representations, enhancements in knowledge, and the extent to which the game influences pro-environmental behaviors.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0200.003

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.

Opus teacher head0.058
GPT teacher head0.300
Teacher spread0.242 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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