Bibliographic record
Abstract
This article aims to investigate what are the internal and external marking traits of indie games. Building up on previous efforts from other scholars, we developed a mix method research approach relying on interviews with indie game developers and a quantitative survey. Rather than trying to “re-invent the wheel” by proposing a new definition for the term, we attempt to map out what are the significant distinctive factors present in contemporary indie game from the perspective of developers and non-developers alike, while also discussing the changes of meaning it might have been subject to over time. We found that the determiningtraits of what allows one to perceive a game as indie change over time,andthat,despite thecorefact thatcreative independence remainsthe central feature of all indie games, the conditions for achieving this independence appear to be rather flexible, especially when it comes to issues of funding and publishing agreements. Additionally, our findings point to the term "indie" as being highly mutable and reliant on temporal and contextual aspects, with the qualities that divideindie fromnon-indie games being more akin to a continuum than something rigidly binary.
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 | 0.008 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.005 | 0.030 |
| Scholarly communication | 0.012 | 0.015 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".