Exploring the Cybersex Phenomenon in the Philippines
Bibliographic record
Abstract
Abstract In its “Philippine Information Society” discourse, the State promotes Filipino service‐based ICT skills while condemning other “offensive” and “illegal” activities, such as cybersex. This dichotomy fails to capture the complex nature of the cybersex phenomenon, and accordingly, the varied lived experiences of individuals in the context of an emergent “Information Society.” We wish to broaden the discursive space by adopting the affective labor perspective and showcasing cybersex narratives that traverse themes of exploitation, negotiation, resistance, and agency in ICT use. Using two case studies, we illustrate how cybersex is experienced, organized, mediated, and made meaningful. We also describe how laborers are inscribed in mechanisms of surveillance and control, as they develop counter‐measures to compromise, challenge or take advantage of these mechanisms. Our analysis reveals that cybersex laborers create value, not just in monetizing their labor, but also in pursuing autonomy, personal development, and kinship‐oriented care. The lived experiences of cybersex laborers also produce new and potent forms of bio‐politics. These multi‐faceted narratives problematize the State‐sponsored ICT discourse. On one hand, laborers embody the impositions made upon service‐based labor by the global digital economy: rudimentary technological skills, the ability to speak English, the ability to empathize and foster customer relations. On the other, their exclusion engendered the refusal to be subjected to the standards and prerequisites of the legitimate, “formal” digital economy. Cybersex's anomalous position, we contend, is a reflexive by‐product of the neoliberal digital economy that puts premium less on ICT for development and more on labor that serves, foremost, ICT for capital.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.010 | 0.012 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".