Does the Situation and/or Caregiver-Child Relationship Influence Perceptions of Intentionality When a Child is Hurt?
Bibliographic record
Abstract
This study will explore possible variables underpinning cases where women have been wrongfully convicted of harming a child when no crime actually occurred. To do this, we created vignettes where a caregiver (of different relationships to the child) called 911 because a child was hurt (in different scenarios, all inspired by actual documented cases of wrongful conviction). One possible reason that women are more likely to be wrongfully convicted in these situations is simply because they are more likely to be in these situations (i.e., caring for children). Thus, first we are testing whether people are more likely to picture women in these situations than men. In addition, parents—particularly mothers—have been wrongfully convicted in these scenarios. Thus, second, we are testing if participants' beliefs about the involvement of mothers and fathers in childcare responsibilities in general, and/or childcare emergency situations in particular, predicts the likelihood that they pictured the parent in the vignettes as a woman or a man. In addition to the research questions described above, we are using this study to pilot test stimuli. For pilot testing, participants will be shown five vignettes of five different situations that led to a 911 call where a child was injured, with different caregiver-child relationships in each vignette (and relationship counterbalanced across all vignettes across participants). These vignettes, and the caregiver-child relationships, were created based on real Canadian cases of wrongful conviction where a child died or was injured, but no crime actually occurred (i.e., the death was due to natural causes or was an accident). After reading each vignette (matched with a different caregiver-child relationship, randomized across participants), participants will be asked about: a) perceived caregiver demographics, b) perceived caregiver-child relationship closeness, c) violation of expectations, d) moral agency, e) suspiciousness, and f) willingness to treat the caregiver as a suspect. Other than perceived caregiver gender, these other dependent variables are for pilot testing only. We will be exploring the impact of the different situations and relationships on these variables, and selecting stimuli for future studies based on the findings (e.g., selecting vignettes that differ in suspiciousness vs. selecting vignettes that do not differ in suspiciousness). After seeing all five vignettes, participants will also be asked questions regarding perceptions of what caregiving role spends the most time raising children and/or responsible for handling emergency situations involving children. The items regarding parents will be used for one of our planned analyses, but all relationships from the vignettes were included for exploratory purposes to help inform stimuli selection for future studies and/or interpretation of the pilot testing findings.
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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 | 0.005 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".