Hispanic Intermarriage, Identification, and U.S. Latino Population Change<sup>*</sup>
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
Objective. This article examines the neglected role of Hispanic intermarriage and identification on Hispanic population change and Hispanic ethnicity. Methods. A trend analysis of Census data produced rates of Hispanic intermarriage and identification as Hispanic by children of intermarried Hispanics. These rates are applied to a projection model of Hispanic population change to 2025. Results. Hispanic intermarriage has been fairly stable and high, at about 14 percent. Almost two‐thirds of children of intermarried Hispanics are identified as Hispanic. The Hispanic population in 2025 is larger by almost 1 million when Hispanic intermarriage and identification rates are included in population projections. Conclusions. Failure to consider Hispanic intermarriage and identification may lead to erroneous conclusions about components of Hispanic population growth. Intermarriage and the propensity of “part‐Hispanics” to identify as Hispanic will be significant contributors to future Hispanic population growth, with implications for the meaning of Hispanic ethnicity and ethnic‐based public policies.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| 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 it