Resilience: Safety in the Aftermath of Traumatic Stressor Experiences
Bibliographic record
Abstract
The relationship between adverse experiences and the emergence of pathology has often focused on characteristics of the stressor or of the individual (stressor appraisals, coping strategies). These features are thought to influence multiple biological processes that favor the development of mental and physical illnesses. Less often has attention focused on the aftermath of traumatic experiences, and the importance of safety and reassurance that is necessary for longer-term well-being. In some cases (e.g., post-traumatic stress disorder) this may be reflected by a failure of fear extinction, whereas in other instances (e.g., historical trauma), the uncertainty about the future might foster continued anxiety. In essence, the question becomes one of how individuals attain feelings of safety when it is fully understood that the world is not necessarily a safe place, uncertainties abound, and feelings of agency are often illusory. We consider how individuals acquire resilience in the aftermath of traumatic and chronic stressors. In this respect, we review characteristics of stressors that may trigger particular biological and behavioral coping responses, as well as factors that undermine their efficacy. To this end, we explore stressor dynamics and social processes that foster resilience in response to specific traumatic, chronic, and uncontrollable stressor contexts (intimate partner abuse; refugee migration; collective historical trauma). We point to resilience factors that may comprise neurobiological changes, such as those related to various stressor-provoked hormones, neurotrophins, inflammatory immune, microbial, and epigenetic processes. These behavioral and biological stress responses may influence, and be influenced by, feelings of safety that come about through relationships with others, spiritual and place-based connections.
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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 | 0.001 | 0.001 |
| 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 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.002 |
| 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".