Bibliographic record
Abstract
In proposing the 2017 conference theme, "Making Sense of Humanity in a Posthumanist Age," our intention had been to mark the 30 th anniversary of Bernard Williams' 1987 Stanford Lecture, "Making Sense of Humanity." We invited authors to consider what remains of "humanity" or "the human" in a time when artificial intelligence, sophisticated robotics, and radical shifts in scientific, social, legal, and political thought have blurred the boundary between the human and non-human. When we posted the call for papers, the US presidential election had not yet happened, and most of us had no idea how urgent the question of what remains of humanity would become, as dehumanizing rhetoric became a regular feature of campaign rallies and reports on the nightly news. In the weeks leading up to our meeting, PES members from countries named in the then-newly-instated travel ban faced uncertainty about whether they would be allowed entry into the US to attend the conference or whether they would be turned away at the border. Some non-US-based members declined to cross the border as a matter of conscience, and others felt torn about whether to attend.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".