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Record W7056719117

Escorts Online: Effects of Policy on Sex Work through Digital Spaces

2021· other· en· W7056719117 on OpenAlexaboutno aff

Bibliographic record

VenueYork University Digital Library (York University) · 2021
Typeother
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsSex workHarmWork (physics)Sex workersThe InternetGovernment (linguistics)Safer sexFrame (networking)
DOInot available

Abstract

fetched live from OpenAlex

In April 2018, the Trump Administration approved two acts that frame sex work as human trafficking. Subsequently, the Federal Bureau of Investigation seized popular adult personals site, Backpage.com, used by Canadian and American sex workers. This led to the increase in censorship of online spaces, which sex workers require to safely conduct their independent business through advertising, processing secure transactions, and maintaining safe communication with clients and the sex work community. My work aims to understand how these changes have explicitly impacted sex workers as they advertise and communicate their services, working predominantly as escorts in Canada and the United States. Governmental documents and laws like Bill C-36/PCEPA and SESTA/FOSTA, which claim to save exploited populations, may harm autonomous citizens making a living through stigmatized labour by seizing their resources and forcing them to use outdated, unsafe methods of business and communication. Most, if not all, of these regulations are developed without the input of sex workers or relevant empirical evidence. Through interviews with current sex workers in Southern Ontario and an overview of ads, a deeper understanding of the communication practices of consensual sex work, its fight for decriminalization, and the importance of the Internet is reached.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.108
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0350.000

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 head0.007
GPT teacher head0.188
Teacher spread0.180 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations1
Published2021
Admission routes1
Has abstractyes

Explore more

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