Fit or fitting in: deciding against normal when reproducing the future
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
‘Normal’ is a contentious term. Descriptively, ‘normal’ represents ‘what is’ as a statistical average. However, the term also represents normative or prescriptive content about what is ‘right’ or ‘what should be’. Correspondingly, abnormality is a deviation from the norm. It is both a factual exception to the average and a value judgement about what is a ‘wrong’ state of being. Pursuing ‘normal’ or deciding against it can be a defining moment in the high technology environment of assisted reproduction. Here, we explore notions of normalcy articulated through legal and policy regimes around screening and testing of gamete and embryo donors. We draw on the work of disability scholars and the diversity of responses to the idea of normal that were registered by four women interviewed in our studies. Three of the interviewees had used or were intending to use donated gametes and the fourth had intended to donate her embryos. We demonstrate how the choice of a particular donor may reveal ingrained or structural prejudice that reconstructs difference as disability. Equally, however, it may reveal a multitude of ways in which difference or deviation from a normative standard is incorporated as a normal part of family formation.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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