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
In Motive Disposition Theory, the affiliation motive describes our need to form mutually satisfying bonds, whereas the power motive is the wish to influence others. To understand how these social motives shape play experience, we explore their relationship to Self-Determination Theory and Flow Theory in League of Legends. We find that: higher intimacy motivation is associated with greater relatedness satisfaction, autonomy satisfaction, enjoyment, and the flow dimension of absorption; higher prosocial motivation with more effort invested and the flow dimension fluency of performance; and higher dominance motivation with lower relatedness satisfaction but higher competence satisfaction and increased flow in both dimensions. We demonstrate that in addition to being driven to satisfy universal needs, players also possess individualized needs that explain our underlying motives and ultimately shape our gaming preferences and experiences. Our results suggest that people do not merely gravitate towards need-supportive situations, but actively seek, change, and create situations based on their individualized motives.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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