Barriers to Medicaid Participation among Florida Dentists
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Finding dentists who treat Medicaid-enrolled children is a struggle for many parents. The purpose of this study was to identify non-reimbursement factors that influence the decision by dentists about whether or not to participate in the Medicaid program in Florida. METHODS: Data from a mailed survey was analyzed using a logistic regression model to test the association of Medicaid participation with the Perceived Barriers and Social Responsibility variables. RESULTS: General and pediatric dentists (n=882) who identified themselves as either Medicaid (14%) or Non-Medicaid (86%) participants responded. Five items emerged as significant predictors of Medicaid participation, with a final concordance index of 0.905. Two previously unreported barriers to participation in Medicaid emerged: 1) dentists' perception of social stigma from other dentists for participating in Medicaid, and 2) the lack of specialists to whom Medicaid patients can be referred. CONCLUSIONS: This study provides new information about non-reimbursement barriers to Medicaid participation.
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.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it