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 dissertation is an exploration of the various ways in which knowledge practitioners come to know about a subject. Using four case studies of marine experts--government-based invertebrate biologists, a university-based team of contaminant ecologists, Kwakiutl (or Kwakwaka'wakw) First Nations (Native American) clam diggers, and Nuu Chah Nulth First Nations clam diggers--I explore the processes and practices by which these practitioners produced knowledge about clams. The case studies are based on ethnographic research I conducted between 2003 and 2005. Drawing on tenets espoused by the Strong Programme in the Sociology of Science, I use a balanced (symmetrical) framework to compare the 4 sets of knowledge practitioners' social relations with their peers, the signs they use as evidence, the methods by which they order and summarize observations, their relationship to what they come to know, their interests, and the assumptions they make when drawing inferences. My theoretical arguments build on literature drawn from a wide spectrum including works from the sociology of science, sociology of culture and cognition, cognitive anthropology, cognitive psychology, and human ecology. Themes running throughout the dissertation include standardization, precision, the situated body and cognition, community, temporality, and multiplicity.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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