Sacred cites: Engaging the spiritual in ethnographic knowledge (re)production
Bibliographic record
Abstract
In this article I offer a Black feminist sacred citational praxis supported by considerations of how subjectivity, relationality, and epistemology speak to questions, such as: which voices contribute to the stories we tell, the arguments that we make, and what is our responsibility to marking and naming those voices? Certainly, the calling of academic names, those thinkers and scholars recognized in academia largely through peer-reviewed writings, is both commonplace and normative. This includes both people who are living and those who have passed. That is, part of our accepted normal praxis is being in conversation with the dead. Yet largely we don’t speak of the “normative” citations as a spiritual practice, or recognize the naming, quoting, and reproducing of people’s voices after they have passed on in that vein. What if we did? What would that look like?
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 | 0.061 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.017 | 0.055 |
| Scholarly communication | 0.015 | 0.018 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".