Achieving status and reducing loneliness during the transition to college: The role of entitlement, intrasexual competitiveness, and dominance
Bibliographic record
Abstract
Abstract Although many emerging adults feel lonely and struggle to gain status during the college transition, it remains unclear whether certain personality traits facilitate this transition. Using a longitudinal design, we investigated whether status‐related traits—namely, entitlement, intrasexual competitiveness, and dominance—related to the development of status in 91 first‐year college students (Mage = 18.15, SD = 0.44) transitioning to a novel college environment. We also examined whether status‐related personality traits moderated the degree to which status related to loneliness. As hypothesized, only students high in intrasexual competitiveness experienced increases in subjective dorm status across the year. In addition, students exhibiting average or low entitlement experienced decreases in loneliness over time, whereas high entitlement was related to consistently low loneliness. Finally, higher subjective dorm status was related to lower loneliness only for less dominant students, as assessed by both self‐ratings of trait dominance and raters’ judgments of facial dominance from photographs. Using a real‐world context of status development, these results suggest that status‐related personality traits may influence students’ ability to experience higher status and modulate the relation between subjective status and loneliness.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".