Bibliographic record
Abstract
Compassionate love, generally defined as giving oneself for the good of another, has been receiving increased attention, especially in the context of romantic relationships. The purpose of the present research was to examine compassionate love "where it begins," namely, in the family. Seven studies were conducted to test the hypothesis that compassionate love would be correlated with various kinds of beneficence in familial relationships, including parent-child (Studies 1 and 2) and adult child-parent relationships (Studies 3-7). Levels of compassionate love and beneficence varied somewhat, depending on the gender of the parent and the child (e.g., adult children reported more compassionate love for their mother than their father). Across relationships, there was strong support for the main prediction that compassionate love would be associated with beneficence, such as willingness to sacrifice, responsive caregiving, and the provision of support. However, it was not the case that compassionate love was negatively associated with variables that were expected to be antithetical to beneficence (e.g., caregiving motivated by obligation). It was concluded that it is important to promote compassionate love where it begins-in the home-given its strong associations with other-oriented, prosocial motivations and behaviors. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".