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.
Bibliographic record
Abstract
This article relates to the 2018 CSDH/SCHN conference proceedings. This paper outlines Michael Iantorno’s and Melissa Mony’s experiences with quantitative game analysis by summarizing the first year of development of the prototype ludomusicological database GameSound. To further the discussion, this article also summarizes and analyzes the work of fellow digital humanities scholar Jason Bradshaw, who applied intriguing types of tool-based analysis to <em>BioShock Infinite</em>. To conclude, the paper hypothesizes where this type of research could lead in the future: both for GameSound and for other projects using similar methods and methodologies. <strong>Résumé</strong> Cet article présente les expériences de Michael Iantorno et de Melissa Mony faites avec des analyses de jeu quantitatives, en résumant la première année de développement de la base de données prototype ludomusicale GameSound. Pour approfondir la discussion, cet article résume et analyse également l’oeuvre de Jason Bradshaw et de Dr. Adrienne Shaw, qui emploient des types intrigants d’analyses de jeu quantitatives et qualitatives dans leurs propres projets, respectivement la <em>BioShock Infinite and Feminist Theory : A Technical Approach et The LGBTQ Video Game Archive</em>. Pour conclure, cet article formule une hypothèse concernant l’avenir de ce genre de recherche : non seulement pour GameSound mais aussi pour d’autres projets qui se servent de méthodes et de méthodologies similaires. <strong><br /></strong> <strong>Mots-clés:</strong> études de jeux; la ludomusicologie; humanités numériques; recherche quantitative; bases de données
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it