Managing my shame: Examining the effects of parental identity threat and emotional stability on work productivity and investment in parenting.
Bibliographic record
Abstract
We identify parental identity threat as a blended work-family experience (i.e., when the family domain becomes a salient aspect of the work domain) that prompts working parents to attend to their parenting identities while at work. By integrating theoretical arguments related to role identities, self-conscious emotions, and identity maintenance, we propose that parental identity threat provokes working parents' shame, which then results in disparate cross-domain outcomes in the form of reduced work productivity and enhanced investment in parenting. We further explain that emotional stability serves as a first-stage moderator of the proposed mediated relationships. Specifically, working parents with higher (vs. lower) emotional stability respond to parental identity threat with weaker shame reactions that then lessen the effects onto work productivity and investment in parenting. We tested our predictions across three studies: an experiment, a multisource field study involving working parent-spouse dyads, and a time-lagged experience sampling study across 15 days also using working parent-spouse dyads. Altogether, our findings generally support our predictions. Theoretical and practical implications and future direction are discussed. (PsycInfo Database Record (c) 2022 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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".