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The Haunted School on Horror Hill

2010· book-chapter· en· W2477873741 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAdvances in game-based learning book series · 2010
Typebook-chapter
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsCentrale des Syndicats du QuébecBrock University
Fundersnot available
KeywordsAdventureThe RenaissanceClass (philosophy)Computer scienceThe InternetMultimediaProcess (computing)World Wide WebVisual artsArtArt historyArtificial intelligence

Abstract

fetched live from OpenAlex

As gaming technology for personal computers has advanced over the last two decades, the text-adventures that predominated in the 1980s ceased to be commercially viable. However, the easy availability of powerful authoring systems developed by enthusiasts and distributed free over the Internet has led to a renaissance in text-adventures, now called “Interactive Fiction.” The educational potential in playing these text-based games and simulations was recognised when they were first popular; the new authoring systems now allow educators to explore the educational potential of creating these works. The authors present here a case-study using the ADRIFT authoring system to create a work of interactive fiction in a split grade 4/5 class (9 and 10 year-olds) in Quebec. They find that the process of creating the game helped improve literary and social skills amongst the students.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.992
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.269
Teacher spread0.261 · 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