Mission unreachable: How Jaman Is shaping the future of on-line distribution
Bibliographic record
Abstract
Perhaps the most innovative of all independent OLD ventures specialising in ROW content is Jaman. Founded in 2007 by IT entrepreneur Gaurav Dhillon, and based in San Mateo, California, Jaman is a quality specialist distributor of non-Hollywood films. As of late 2010, Jaman had 1.8 million registered users and attracts viewers from most countries in the world. 75% of all use is generated from outside the U.S. Jaman does very well in English speaking parts of the world, particularly current and former Commonwealth countries. The United Kingdom accounts for 29% of users, North America (U.S. and Canada) 26%, and India represents 23%. Jaman is sometimes referred to as ‘social cinema’: a website which brings together the critique and review of a cinephile website (the forums of Rue-morgue.com for cinefantastique movie fans for example) with the social interaction, community and functionality of a social media site (for example Facebook.com). Jaman could be considered a pioneer in this space; a first mover in wrapping commercial movie downloading in an interactive social experience.
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 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".