Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper develops a theoretical approach for understanding how the census has not only played a role in constructing population (census making) but has simultaneously created subjects with the capacity to recognize themselves as members of a population (census taking). The ‘population’ is now generally considered something that is not discovered but constructed. But what is neglected is that the population is also produced one subject at a time. The paper provides an account of census taking as a practice of double identification (state-subject) through which subjects have gradually, and fitfully, acquired the capacity to recognize themselves as part of the population through the categories circulated by the census (subjectification) and the state has come to identify the subject and assemble the population (objectification). The approach is elaborated in an account of a particular moment in the creation of census subjects, the self-identification and discovery of individuals as ethnically ‘Canadian’ in the early part of the twentieth century. Through this account I suggest that the capacities and agencies of being a census subject are connected to citizenship and the claiming of social and political rights.
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.
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) | 0.007 | 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 it