Understanding Fear in Therapeutic Residential Care
Bibliographic record
Abstract
In therapeutic residential care (TRC), both children and staff sometimes experience fear. Little scholarship in our field has integrated the substantial contemporary research literatures on fear as a biopsychosocial phenomenon. Attending to what is known about how fear works at the individual, organizational, and cultural level is necessary to improve working conditions and quality of care in TRC. This article draws from neuroscience, psychology, and sociology to improve our biopsychosocial understanding of the experience and consequences of fear in TRC. These literatures demonstrate that: 1) Fear is a potentially adaptive response to threat involving conscious and nonconscious neural processes; 2) Fear (and all emotion categories) is shaped by culture and therefore varies; 3) Instances of fear are constructed based on our predictions about the future rather than being reactions to experience; 4) Individuals vary in their ability to experience fear and recognize it in others, and this variation is related to other capacities of great interest in child welfare; and 5) Children and staff learn to perform and experience emotions—including fear—through explicit and implicit education in the feeling rules of their organization and broader culture. We suggest actions organizations can take now to help children and staff better understand fear and develop more adaptive responses to it. We propose directions for future research on fear in TRC that can guide efforts to make child welfare involvement a less threatening experience for children, their families, and the people who care for them.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".