MétaCan
Menu
Back to cohort
Record W4300079527 · doi:10.3138/jeunesse.8.1.154

Pedagogical Encounters with <i>Inanimate Alice</i>: Digital Mobility, Transmedia Storytelling, and Transnational Experiences

2016· article· en· W4300079527 on OpenAlexvenueno aff
Cheryl Cowdy

Bibliographic record

VenueJeunesse Young People Texts Cultures · 2016
Typearticle
Languageen
FieldHealth Professions
TopicDigital Storytelling and Education
Canadian institutionsnot available
Fundersnot available
KeywordsNarrativePrivilege (computing)Alice (programming language)SociologyExperiential learningStorytellingReading (process)Visual artsPedagogyMedia studiesPsychologyArtComputer scienceLinguisticsLiterature

Abstract

fetched live from OpenAlex

Inanimate Alice (IA) is a digital novel that employs strategies of transmedia and game-based storytelling in order to appeal to the “born-digital” generation. Using a simple episodic narrative structure, IA moves readers around the globe as Alice travels to various locations and homes in different national contexts. Thematically, the narrative both allays and raises anxieties about children’s experiences of mobility and migration. Incorporating literary and cultural analysis with multimethod qualitative research, this article investigates the ways in which children’s understandings of their practices of mobility are shaped by transmediation and their reading experiences of IA. It also considers how adults and young people might work together in their encounters with such texts to create “animated learning” scenarios that privilege what I call alternative pedagogies of mobility, in which adult-child hierarchies are disrupted and physical and virtual movements are considered essential to experiential, reflective learning.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.014
Scholarly communication0.0080.005
Open science0.0010.010
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.037
GPT teacher head0.355
Teacher spread0.318 · 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 designQualitative
Domainnot available
GenreEmpirical

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
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueJeunesse Young People Texts CulturesSame topicDigital Storytelling and EducationFrench-language works237,207