The Millennial ‘Meh’: Correlated Groups as Collective Agents in the Automobile Field
Bibliographic record
Abstract
Abstract Explanations for field change emphasize the role of purposeful strategic actors, paying little attention to uncoordinated but cohesive social groups, despite their profound impacts on fields ranging from autos and news to politics. Using a mixed methods approach, we study Millennials’ driving behaviours, focusing on the role of generation cohorts as field actors. Combining in‐depth qualitative analysis with an original nationwide survey ( N = 2,225) we find that Millennials exhibit significantly different driving behaviour than earlier generations, driving for roughly 8 per cent fewer trips. These differences are primarily due to their attitudes, not, as commonly presumed, socio‐economic factors. Our results contribute to theory on fields and collective actors. First, we identify a new field phenomenon, correlated groups , uncoordinated actors behaving as collective agents due to shared experiences and characteristics. Second, we identify four mechanisms through which correlated groups impact fields: correlated imprinting, cohorts as conduit, cohort myth apathy, and cohort myth creation .
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".