Rhetorical Historians and the Role of Gender and Commodification of the Past
Bibliographic record
Abstract
Rhetorical history is a concept that describes the strategic uses of the past in organizations. To date, this literature has not defined the identities, roles and positions of the producers of such rhetorical histories. Our paper challenges the absence of the “rhetorical historian” through a historical-archival study that introduces the earliest known heritage management firm in the US, HM Baker & Associates (HMBA). The firm was run by two women whose pioneering work in establishing the field has been largely forgotten, despite widespread recognition at the time. HMBA employed variations of common rhetorical history practices and generally worked with mid-size firms as they were unable to be hired by larger corporate clients. Our study identifies the exclusion of female rhetorical historians from the professional markers of success, which led to their firm working predominantly with less well-endowed companies, developing relatively cheap, popular and “crappy” uses of the past. These are rendered invisible in the rhetorical history literature as it elides gender and status of the producers of rhetorical histories in favour of focusing on generalisable processes. We argue that gender is an absent presence in this literature which consistently selects male uses of the past as being of higher value and thus ignores the limited involvement of women as historical producers due to the “crappiness” of their rhetorical histories that we attribute to gender-based exclusion.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.007 | 0.035 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".