Bibliographic record
Abstract
All human societies remember their ancestors but they do so in very different ways. Where there is no writing, memory of one's forebears is evoked by shared reminiscences, mementos or ceremonies, but never by rereading their letters or obituaries. In some places, ancestors are recalled by donning masks, by imitating their gestures and by going into a trance. We remember our dear departed when we pay a visit to the cemetery. But cemetery visits, as we know them, are essentially a nineteenth-century innovation. Memorial practices change through the ages. The role played by monuments and processions, for example, has varied historically, not only in commemorating one's immediate ancestors, but also in the way the collective memory of societies is mobilized. Historical change in social practices of recall is not limited to ancestral memory. Among non-literate people, rules and regulations cannot be recalled by consulting written documents, though consultation of elders is common. There may also be specialists in memory whose services may be required even after the introduction of writing. Ancient Greece had the institution of the mnemon , a person whose job it was to remember religious or legal matters relevant to decision-making and jurisprudence. Roman politicians and lawyers were known to own graeculi , ‘little Greeks’, who were intellectually trained slaves that were also required to memorize social and technical information so that they could prompt their masters during court sessions and political or social events.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.023 |
| Scholarly communication | 0.010 | 0.018 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".