Bibliographic record
Abstract
The Art and Science of Social Connection by Kasley Killam presents a case for better understanding individual health by ensuring that the social aspect is considered as a significant component of health in addition to the physical and mental aspects. Killam states that social health consists of an individual’s sense of belonging, the strength of relationships, and meaningful connections. By drawing from years of evidence building, Killam argues that social health is fundamental for one to truly flourish and prosper in their life as people who have stronger social health are shown to have higher quality of life, emotional resilience, and longevity. The Art and Science of Connection is an award-winning, 288-page book that takes the reader through not only understanding social health but also learning how to apply a framework that offers practical strategies to strengthen one’s own social health. As part of discussing key concepts, Killam, an internationally recognized expert in social health, redefines what it means to be healthy, offers a critical lens in examining the types of relationships people may have, including how each type may affect social health differently, argues for making social health a priority by being consistent in strengthening social muscles, and unveils ways that individuals can flourish together by joining a growing movement in social health. The aim of this review was to spotlight Killam’s book as a thoughtful approach for thinking about ways through which everyone can reach optimal health by connecting with others and strengthening their relationships.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.022 | 0.012 |
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".