Personality differences between birth order categories and across sibship sizes
Bibliographic record
Abstract
We examined associations of self-reports on the HEXACO Personality Inventory—Revised (HEXACO-PI-R) with birth order category and sibship size, controlling for participant sex and age. In a first sample ( N > 700,000 online adults, mainly from English-speaking countries), Honesty-Humility and Agreeableness both showed the highest means for middle-borns, followed in order by last-borns (youngests), firstborns (oldests), and only children, with differences between middles and onlys of d ≥ 0.20. The same result was replicated in a similar but smaller second sample ( N > 70,000) in which sibship size was also assessed, thereby allowing birth order differences to be separated from sibship size differences. In that sample, Honesty-Humility and Agreeableness showed higher means with larger sibship sizes, with differences between sibship sizes of 1 and 6+ of d = 0.30 and d = 0.36, respectively. Controls for upbringing religiousness and current religiousness reduced these differences by about 25%. Within sibship sizes, birth order differences in these dimensions were considerably smaller but oldests remained up to d = 0.10 lower than middles and youngests. Openness was d ≈ 0.10 higher for onlys than for non-onlys collectively, and within sibship sizes, Openness was d ≈ 0.10 higher for oldests than for middles and youngests.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".