Bibliographic record
Abstract
In the following research I discuss a number of issues which are fundamental to my understanding of how best to reconstruct past human events from the methodological outlook of a legal historian. Herein one will find an explanation of and justification for the various aspects of the historical method and philosophy I employ in my larger research area involving the Roman Emperor Constantine, the Christian Church, and state sovereignty. I also discuss some lines of intersection between modern day legal actors and historians to show how their common goal of getting to the truth of a question may encourage the former to consider using some of the same hermeneutical tools as the latter. History as a discipline has always been primarily concerned with humans and their actions, and this has been noted by many historians: Marc Bloch and R.G. Collingwood come to mind as being two of the strongest proponents of this dictum. Since the field of human events in the past is so large, I suggest it behooves us, then, not to confine ourselves too narrowly within our investigations concerning the hermeneutical tools we employ in the study of the multivariate ways that humans have acted and existed since their appearance some two-hundred thousand years ago: and to this end I employ Sub specie aeternitatis as my research’s inclusive-contextual raison d'être. This perspective requires an acknowledgment that scholarly observations about the reality of the human condition from other disciplines must be employed in the effort to be as wide-ranging in our research method gathering as the historical method will allow: and thus a number of key contributions from authors in various academic fields will be discussed to highlight the relative importance of their ideas to my own. I will be using examples within my own area of study to engage these ideas and this will better acquaint the reader with how I approach historical data. This discussion will be purposely focused on the foundational ideas upon which my own historical method is based. This will enable the reader to better appreciate how it is that I as a historian come up with suggestions about what it was in history that most likely happened. I conclude that as a historian my highest goal must be to offer an imaginative re-construction of an historical event and its concomitant personages which is based on extant data, but which also must engage in a participatory re-thinking pursuant to the motivations of the characters involved such that the end result can be read as an intelligible whole.
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 | 0.034 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.004 |
| Science and technology studies | 0.008 | 0.077 |
| Scholarly communication | 0.014 | 0.024 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.009 | 0.017 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".