Click farm platforms
Bibliographic record
Abstract
The article analyses work on click farm platforms in Brazil and Colombia. It argues that work on these platforms updates and renews the historical informality of work in Latin America. Drawing on click farm ethnography, worker interviews and digital ethnography on WhatsApp and Facebook groups and Youtube channels, the research highlights: first, the cultural marks of Brazil and Colombia in the interactions between workers, typical of Latin American digital culture; second, the role of Youtubers as skill makers, responsible for the initiation of workers into click farm platforms and the circulation of neoliberal and entrepreneurial ideology; third, practices and discourses relating to reselling accounts, photos and bots as a new version of the historical resale markets in the region; and fourth, the boundaries between informality and illegality at work on click farm platforms. The article argues that, in addition to informal work that preceded and is connected to work on click farms, informality gains new dimensions with work on click farms, with the platformisation of labour representing an articulation between the old informality and new market practices and infrastructures.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.037 | 0.004 |
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".