Does the ‘Infoproletariat’ Include Systems Analysts? Organising IT Workers in the Brazilian Banking Sector: Challenges and Opportunities
Bibliographic record
Abstract
As labour struggles around the impact of technology on working conditions heat up across various countries and sectors, myriad studies argue that the technologically based restructuring of workplaces has contributed to increasing precariousness in the new world of work. However, technology workers themselves have often been assessed as resistant to collective organising. This article explores the work experiences of IT workers in Brazil’s banking industry, many of whom are the most sought-after workers in the country — but who, from their own testimonies, confront a range of conditions that could form a basis for strong collective action. We analyse how technology work is organised within the largest private banks operating in the country and reflect on workers’ actual experiences, based on dozens of in-depth interviews, survey responses, and secondary literature. Our primary research objective is to better understand the scope of obstacles confronted by financial sector technology workers in Brazil, wherein may lie the potential for future collective action.
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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 | 0.010 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.013 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".