New business histories! Plurality in business history research methods
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We agree with de Jong et al.'s argument that business historians should make their methods more explicit and welcome a more general debate about the most appropriate methods for business historical research. But rather than advocating one ‘new business history’, we argue that contemporary debates about methodology in business history need greater appreciation for the diversity of approaches that have developed in the last decade. And while the hypothesis-testing framework prevalent in the mainstream social sciences favoured by de Jong et al. should have its place among these methodologies, we identify a number of additional streams of research that can legitimately claim to have contributed novel methodological insights by broadening the range of interpretative and qualitative approaches to business history. Thus, we reject privileging a single method, whatever it may be, and argue instead in favour of recognising the plurality of methods being developed and used by business historians – both within their own field and as a basis for interactions with others.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 it