MétaCan
Menu
Back to cohort

Click farm platforms

2022· article· en· W4312456255 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueWork Organisation Labour & Globalisation · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Economy and Work Transformation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEthnographyWork (physics)Latin AmericansArticulation (sociology)SociologyIdeologyDigital cultureGig economyMedia studiesPolitical sciencePrecarityGender studiesAnthropologyEngineeringLaw

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.912
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.015
GPT teacher head0.248
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it