Bibliographic record
Abstract
Silvia Federici writes, "Starting from an analysis of "body-politics," feminists have not only revolutionized the contemporary philosophical and political discourse, but they have also begun to revalorize the body. This has been a necessary step both to counter the negativity attached to the identification of femininity with corporeality, and to create a more holistic vision of what it means to be a human being." (15) I wonder, what does it mean for my body to live on different land than my parents'? How do I reckon with the gender binary, and with having a body and a gender that exist outside of normative narratives? What does it mean to dig into sexuality in a world of gender-based violence, of body negativity, of sex negativity, of moralism? What does it mean to fully grieve in a culture that obliges the body to be quiet and pretty? It is strenuous to seek embodiment in a world where the body is a site of so much violence and pain. Nonetheless, I am curious, and I am committed to the revalorization of the body as a site of liberation and wholeness. “Water Memory” is the story of the traumas that continue to live in my body—ancestral and current. It is written as an invocation of intimacy partnered with grief. It encourages relationships (with the self and with others) that not only allow, but revel in, the fullest embodiment of the body’s experience. I write from a place of queerness, of transness, as a first-generation Greek/Turk/Uke Canadian with chronic pain and a mood disorder. Yet, I insist, my body is not the enemy.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.560 | 0.271 |
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".