Bibliographic record
Abstract
This convenient case study will explore the impact of not-games on secondary English language arts students in a high school located in a satellite community of a major city of Alberta. These not-games are often free, short, intuitive, and readily available on the Internet, exposing players to novel issues and perspectives. This study examines whether not-games help students learn about literature through a more rhizomatic strategy that encourages reflection about literature via kinaesthetic or haptic experiences that not-games provide, thus making the learning memorable. Two English Language Arts 30-1 classes experienced not-games alongside a novel and short story unit. Those students who presented or wrote on not-games were analyzed for influence. Using the theory of Deleuze and Guattari, not-games can be considered a “minor literature” or a machine of transposition for deterritorializing arborescent approaches to literature by flattening them into a rhizomatic plateau with many entry points, offering nomadic, transversal opportunities to discover new flight lines (Deleuze & Guattari, 1975/1986; Deleuze & Guattari, 1980/1987).
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
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 source (direct Gemma or distilled Codex), 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".