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
As the internet and digital tools become more accessible, video gaming enthusiasts are emerging worldwide. Esports refers to video game competitions involving professional players using acquired skills to win. Nigeria generated an estimated 46.5 million gamers in 2021. This study uses mixed methods to explore the Nigerian esports landscape and the factors that limit its growth. 390 young Nigerian gamers responded to surveys, and four esports entrepreneurs were interviewed. Through the uses, gratifications, and media economics theories, the findings revealed that young Nigerians are participating and earning a living from video gaming across virtual and physical arenas in Nigeria. Other young Nigerians are enthusiastic about esports; however, the industry requires an infrastructural, policy, technical and visibility drive towards actualization. I recommend that actionable steps should go beyond immediate revenue generation by also deepening the development of esports in Nigeria towards sustainable socioeconomic development.
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 | 0.001 | 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 | 0.000 | 0.000 |
| 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