Immigration, Community Integration and Public Health in Colorado's Rocky Mountains: An Overview and its Governance
Bibliographic record
Abstract
This paper explores the link between new immigration to Colorado (USA) mountain communities and public health service access with a case study focus on Lake County, Colorado. It utilizes a combination of key informant interviews—with county commissioners, health providers, locally-based organizations and civic leaders—and focus groups with community members, in order to examine how disparities in access and representation across sub-populations translate into health outcomes. This paper makes several arguments. Specifically, this paper recognizes important efforts taking place within the community to better integrate the Latino population, and to include its input on evolving public health and youth empowerment/well-being initiatives. Nevertheless, the Latino population remains isolated, based on a combination of economic and social factors that structurally limit the participation of the greater Latino population in civic affairs. Certain culturally-relevant attributes, and Latino agency, provide opportunity as well, however, and this paper isolates several pathways through which local governance can merge formal and informal processes in order to better bridge between the self-identified needs and desires of the Latino population and health access and outcomes. The paper concludes with a note on the emerging “socio-economic ecosystem” of Colorado mountain regions, which distinguishes employee-housing communities from resort communities, augmenting disparities in services and deepening the structural exclusion of minority immigrant communities from adequate healthcare. Keywords: immigration, public health, resort-based economies, structural exclusion, environmental health, Colorado
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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 | 0.004 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".