Successful Self-Representation in Cyberspace: Evidence on Russian brides from an internet marriage agency
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, we investigate the factors associated with success in a special marriage market. This marriage market is generated by a marriage agency that arranges meetings between women from the former Soviet Union and men from the United States, Canada and Western Europe. It is the modern version of the mail order bride industry that has successfully migrated to the Internet. Russian women seek partners by providing profiles of themselves on a website. We define success to be finding a suitable match culminating in engagement or marriage. We analyze data on profiles of two groups of Russian women. One group consists of a sample of single women who seek partners, and the second is a sample of women who have successfully found a partner via this method. By comparing these profiles, we are able to identify the factors associated with success in this marriage market. We find that although most of the self-reported information is not significantly different across the two groups, women who report lower weight, speak good English and come from Moscow or St. Petersburg are more likely to find a partner than women who do not. The non-significant findings are interesting as well, as they reveal that age, previous marital status and the presence of children do not matter.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it