Adaptation to Stress: A Common Model and Method to Facilitate Within- and Cross-Cultural Evaluation of Foster Families
Bibliographic record
Abstract
Studies meant to allow “cross-cultural” comparisons may be fatally flawed by the concepts, instruments, and discoveries of one culture being applied uncritically to another (namely, “etic” errors; cf. current discussions and examples in Chand, 2008; Durrenberger and Erem, 2007). Moreover, studies of foster families often disregard the unique ecosystemic environments in which those families are embedded (Lee, 2008). Therefore, this paper describes an overarching family adaptation model meant to resolve the foregoing problems. Secondary analysis of data describing urban Egyptian foster families (Megahead, 2008; Megahead and Cesario, 2008) illustrates the application of this model and suggests its heuristic value: Use of this model and method will allow common understanding of commonalities and differences within and between cultures, while respecting the uniqueness of each. The Family Stress and Adaptation Model focuses on family adaptation as a function of family stressors interacting with family coping resources. Although the framework is thought to apply to all cultures involving families, the variables—adaptation, stressors, and resources—are defined and operationalized emically (that is, the cultural insider’s perspective determines what is to be considered, its nature, and size).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".