Perceived Attitudes Towards Romanticism; A Cross-cultural Study of American, Asian-Indian, and Turkish Young Adults
Bibliographic record
Abstract
The Knox & Sporakowski attitudes toward romantic love scale, a list of 13 desired qualities in a prospective partner, and a demographic questionnaire were distributed to a total of 641 young adults at three international universities in America, Turkey, and India. The sample consisted of 200 American young adults in Western U.S., 223 Turkish college students in Central Turkey, and 218 Indian young adults enrolled at a university in Western India to determine their perceived attitudes toward romanticism. The second objective was to investigate whether age, gender, and parents’ marital status were related to romanticism. A third objective was to examine cultural differences in the American and Turkish respondents’ attitudes about preferred qualities in a potential mate. Results showed that the American young adults were most romantic, followed by the Turkish students, and Indians had the lowest romanticism score. Female college students in all three cultures were significantly more romantic than males. Age and parents’ marital status were not related to romanticism. Cultural differences were found in conjunction to desired qualities in a prospective partner. American and Turkish young adults differed significantly in their attitudes toward the following attributes: having similar political ideologies, being well educated, being affectionate, having a good job, having similar interests, and not having a prior marriage. Gender differences were also found with regard to desired qualities in a potential partner. Males and females differed significantly in their rankings of having a good job, being physically attractive, having similar political ideologies, being well educated, and not having a prior marriage. Implications for researchers and practitioners are discussed.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".