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Record W4245192356 · doi:10.32920/ryerson.14661786.v1

Civic crafting: the potential of Minecraft for municipal civic engagement

2021· preprint· en· W4245192356 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldComputer Science
TopicPersona Design and Applications
Canadian institutionsToronto Metropolitan UniversityUniversity of Alberta
Fundersnot available
KeywordsPublic engagementKey (lock)Civic engagementGame designPsychologyComputer sciencePolitical scienceMultimediaPublic relationsPolitics

Abstract

fetched live from OpenAlex

Minecraft, the popular video game, shows promise as a planning engagement tool: it allows players to experience and manipulate a three-dimensional environment, it is easy to learn and understand, it is engaging and immersive, it is adaptable, and it has already begun to be used for geodesign and planning engagement. However, this game has not yet been studied to determine how it could best be used for this purpose. Using an analysis of key informant interviews, this study seeks to address this deficit and reflect on the ways in which this game could help planners achieve various engagement goals. Key findings in this study address Minecraft’s usefulness as a visualization tool, its role in building trust, the place of play in planning, and the challenges associated with conducting an accessible, interactive online engagement using Minecraft.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.928
Threshold uncertainty score0.624

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.051
GPT teacher head0.295
Teacher spread0.244 · 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

Quick stats

Citations2
Published2021
Admission routes1
Has abstractyes

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