The bittersweet taste of sacrifice: Consequences for ambivalence and mixed reactions.
Bibliographic record
Abstract
People in close relationships often need to sacrifice their own preferences and goals for the partner or the relationship. But what are the consequences of such sacrifices for relationship partners? In this work we provide a systematic investigation of the consequences of sacrifice in romantic relationships, both for the person who gives up their goals as well as for the recipient of these benefits. In 5 studies combining experience sampling and experimental methods, we examined whether performing and receiving sacrifices is linked to the experience of ambivalence, that is, mixed feelings toward a partner. In the last 3 studies, we also examined the specific positive and negative reactions associated with sacrifice. Results revealed that performing and receiving sacrifices are both linked to ambivalence toward a romantic partner. Recipients of sacrifices experienced higher negative mood, guilt, and feelings of indebtedness, but these were accompanied by higher positive mood, gratitude, and feeling appreciated by the partner. Sacrificers mostly experienced negative reactions, such as higher negative mood, frustration, and feelings of exploitation, but they also reported some positive reactions, such as feeling happy from benefitting their partner, proud of themselves for being a good partner, and had increased expectations that their partner would reciprocate the sacrifice in the future. In sum, this work provides the first comprehensive study of the emotional reactions that are triggered by sacrifice and shows that sacrifice is a double-edged sword with both positive and negative consequences. Implications for sacrifice and ambivalence are discussed. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
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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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".