Person-specific priorities in solitude
Bibliographic record
Abstract
People value solitude in varying degrees. Theories and studies suggest that people’s appreciation of solitude varies considerably across persons (e.g., an introverted person may value solitude more than an extraverted person), and solitude experiences (i.e., on average, people may value some functions of solitude, e.g., privacy, more than other functions e.g., self-discovery). What are the unique contributions of these two sources? To answer this question, we surveyed a quota-based sample of 501 US residents about their perceived importance of a diverse set of 22 solitude functions. Variance component analysis reveals that both sources contributed to the variability of perceived importance of solitude (person: 22%; solitude function: 15%). Crucially, individual idiosyncratic preferences (person by solitude function interaction) had a substantial impact (46%). Further analyses explored the role of personality traits, showing that different functions of solitude hold varying importance for different people. For example, neurotic individuals prioritize emotion regulation; introverted individuals value relaxation; and conscientious individuals find solitude important for productivity. These results show that people value solitude for idiosyncratic reasons. Scientific inquiries on solitude must consider the fit between a person’s characteristics and the specific functions a solitary experience affords. This research suggests that crafting or enhancing positive solitude experiences requires a personalized approach.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".