Hispanic Intermarriage, Identification, and U.S. Latino Population Change<sup>*</sup>
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.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".