Bibliographic record
Abstract
More than one‐quarter of Americans say they are more stressed this holiday season than in 2023, citing financial concerns and missing loved ones, according to a Nov. 25 news release from the American Psychiatric Association (APA). As the winter holidays approach, 28% of Americans say they are experiencing more stress related to the holiday season than they did last year, but the causes of their stress vary. A few of the top stressors identified were affording holiday gifts (46%), grieving a loss/missing a loved one (47%) and dealing with challenging family dynamics (35%). More than half of 18‐ to 34‐year‐olds (54%) reported being “very” or “somewhat” worried about affording holiday gifts, whereas only 38% of those 65 and older felt the same way. Although 2024 is an election year, only 23% of respondents said they were worried about discussing politics or current events with family over the holidays, consistent with what was reported in 2023. Along party lines, 30% of Democrats were concerned about talking politics at the holiday dinner table, but only 21% of Republicans shared their concern, and that number dropped to 17% for Independents. These results were drawn from the APA Healthy Minds Monthly Poll, which was conducted by Morning Consult, a business intelligence company, on Nov. 16‐17, 2024, among 2,201 adults.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.267 | 0.142 |
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".