Honoring our dead: text mining a century of academic obituaries in The Lancet
Bibliographic record
Abstract
In consecrating the lives of the deceased, obituaries offer a unique window into the values and social dynamics of academic communities. Here, we conduct a preliminary textual analysis of 5,069 obituaries published in The Lancet between 1850 and 2019 to understand how the genre has evolved in response to unfolding history and changing academic norms. We find that the rate of obituaries varied over time, peaking immediately following World War 1. On average, the sentiment of obituaries has increased over time. Largely, obituary text describes the life, accomplishments, and accomplishments of the deceased, although the prominence of these topics has changed over time. For example, discussion of military service was most prominent in the early 1900s, whereas more recent obituaries instead spend more time detailing the deceased’s scholarship and academic career. Ours is the first large-scale text analysis of academic obituaries. In conducting this analysis, we revealed how this genre of writing has evolved over the past century in response to conflicts and changing conventions. Moving forward, we aim to leverage obituaries to better understand how academic virtues evolved, and how they differ by gender, discipline, and more.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".