Immigration Related Trauma Among Haitians: Barriers to Treatment and the Role of Faith in Creating Resiliency
Bibliographic record
Abstract
The topic of this writer’s dissertation is immigration-related trauma among Haitians, barriers to treatment, and the role of faith in creating resiliency. The purpose of this qualitative push and pull hermeneutic phenomenological study is to understand the lived experiences of people who have immigrated to the United States (US). To better understand these lived experiences, it is imperative to also examine the experiences of Haitian immigrants from the gateway countries of Brazil, Chile, Canada, and the Dominican Republic. It is known that a number of Haitians have entered the US directly (legally or illegally) and a great many entered by way of the above gateway countries. As we will later see these countries throughout their histories have adopted laws that welcomed Haitians and later repealed those same laws, creating mass deportations. Through these deportations, many Haitians have undertaken dangerous journeys into the US. This study will evaluate effective treatment in addressing the multidimensional needs of this population, including barriers to treatment and the role the church or religious community can play in creating resiliency amongst this population. Study participants engaged through in-depth semi-structured interviews to explore the lived experiences of these immigrant Haitians. The interviews assessed for possible Post Traumatic Stress Disorder (PTSD) diagnosis or reported symptoms of PTSD as part of participants’ lived experiences. Two sampling methods were utilized: purposeful sampling and snowball sampling. The data analysis method used was the Colaizzi’s method of data analysis, as it requires participants to validate findings to ensure they are accurate and credible.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".