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Occupation · Healthcare Support Occupations

Medical Transcriptionists

SOC 31-9094.00 · 13,479 matched workers · high confidence

Strong Democratic lean
68.3% Democratic, 31.7% Republican

Two-party shares across 13,479 workers in this occupation matched to voter registration records.

68.3%
31.7%
DemocraticRepublican
Imputed
68.9% D · 31.1% R
Includes lean for unaffiliated registrants
Major group
Healthcare Support Occupations
SOC major code 31-0000
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Where Medical Transcriptionists falls

More Democratic than 70% of occupations in Healthcare Support Occupations.

← DemocraticRepublican →Medical Assistants — 69% DemocraticNursing Assistants — 71% DemocraticPhlebotomists — 66% DemocraticOccupational Therapy Assistants — 61% DemocraticPersonal Care Aides — 71% DemocraticHome Health Aides — 68% DemocraticDental Assistants — 62% DemocraticPhysical Therapist Assistants — 56% DemocraticOrderlies — 64% DemocraticVeterinary Assistants and Laboratory Animal Caretakers — 70% DemocraticMedical Equipment Preparers — 60% DemocraticPharmacy Aides — 63% DemocraticPsychiatric Aides — 72% DemocraticMassage Therapists — 65% DemocraticPhysical Therapist Aides — 64% DemocraticHealthcare Support Workers, All Other — 64% DemocraticSpeech-Language Pathology Assistants — 67% DemocraticOccupational Therapy Aides — 55% DemocraticEndoscopy Technicians — 63% DemocraticMedical Transcriptionists — 68% Democratic0%25%50%75%100%
Each dot is one of the 19 other occupations in Healthcare Support Occupations; size scales by worker count. Hover to see names — click to jump.

How this is measured

VRscores estimate the partisan composition of an occupation by linking voter registration records to employment profiles. Each worker is assigned to one occupation per year. The two-party shares above exclude workers with no major-party affiliation.

Read the full methodology or the published Organization Science paper.

Other occupations in Healthcare Support Occupations

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Citation

Kagan, Max; Frake, Justin; Hurst, Reuben (2026). “VRscores: A New Measure and Data Set of Workforce Politics Using Voter Registrations.” Organization Science, 37(2), 444–465.
https://doi.org/10.1287/orsc.2025.20402