Petit Bourgeois Health Care? The Big Small-Business of Private Complementary Medical Practice
Bibliographic record
Abstract
Features of the complementary/alternative medicine (CAM) sector have been under-researched in the academic literature. This study set out to investigate how businesses and business attitudes impact CAM, using the concept of the small business petit bourgeoisie. Data was collected using a two-staged questionnaire and interview survey. Stage one (questionnaire survey) respondents were selected from a telephone directory and consisted of a sample of 426 private complementary therapists from five regional sub-samples. Stage two (interview survey) participants were also selected from a telephone directory, and involved 49 detailed interviews with therapists in three regions in the UK. The following results were obtained: (1) there were similarities between the core characteristics of therapists and their businesses and the petit bourgeoisie mode of operation, (2) therapists were selling goods with market practicality, (3) due to financial insecurity and uncertainty, stress appeared to be evident among therapists, (4) therapists took on several roles in the sector, thus there was a lack of extensive management structures, and (5) due to the diversity and underlying employment trends, certain features of business ownership suggested that private CAM ownership was petit bourgeois. Although the private CAM sector may conflict with the traditional Marxist analysis, it is important in assisting products that were rejected by bigger businesses and public demands neglected by orthodox medicine.(NEE)
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".