Introduction: Metaphors as Meaning and Method in Technoculture
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
Metaphors are critical sites of analysis for feminist scholars of science and technology because of what they both conceal and divulge about the conditions of their historical emergence and the persistence of those conditions. As researchers and editors, we find ourselves oriented to work that takes up the task of contesting uncontested metaphors, considering how metaphor “invades” (Tuck & Yang 2012, 3) and evacuates meaning. This Special Section carries on the dynamic practice in feminist STS of taking the work, and ambivalent potentiality, of metaphor seriously. In this Introduction, we draw together scholarship that informs what we identify as the "metaphor-work" of feminist STS—the work of allegory, myth, metaphor, figurative and associative discourse, and their analysis—as central to the methods by which we make and remake meanings that matter to feminist technocultures. Throughout the metaphor-work collected here, the contributors propose that paradigm change comes through the collective refusal of some metaphors, through the re-evaluation of others, and the introduction of new metaphorical frames and figures to reorient our work.
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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