An Invisibility/Hypervisibility Paradox: The Sociology of Middle Eastern and North African (MENA) Americans
Bibliographic record
Abstract
Research on Middle Eastern and North African (MENA) populations in the United States has been shaped by a fundamental paradox: MENAs are statistically invisible in the administrative data infrastructure yet socially hypervisible in other domains. This review outlines key demographic characteristics of the MENA American population and argues that by addressing the invisibility/hypervisibility paradox through innovative research questions and methods, previous scholarship has advanced sociology in three areas: identity, racialization, and integration. As upcoming changes to federal race and ethnicity standards take effect, the invisibility/hypervisibility paradox may shift as sociologists more easily collect and analyze data about MENA Americans. However, this information may be misused, misinterpreted, or handled unethically without sufficient background context and responsibility to community members. Future research will require data disaggregation to explore intersectional and intragroup minority issues, examination of the evolving content and meaning of MENA panethnicity, and ongoing assessment of the MENA group's relative racial position.
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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 | 0.020 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.029 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".