Bibliographic record
Abstract
This methodological reflection was catalyzed by a research project conducted in suburban Toronto inquiring into youth attitudes to diversity and the changing geography of the suburb. The first methodological dilemma concerns design when so much is still unknown as a research study begins. In addition to methodological adaptability, Wessels addresses the puzzles presented by empirical materials and their affective draw to the researcher. In the pre-analysis stage, although little sense can yet be made of the data and appropriate theoretical tools may not yet have been found, Wessels suggests the need for sufficient researcher time and space to adequately address ‘not knowing’, to read widely, and to adopt a methodology of patient waiting for appropriate and relevant theory. Wessels offers examples of methodological practices that evolved over the course of the research. In particular, ethnographic interviews-while-walking became a kind of walking methodology that finally became a placed compositional performance that included the participation of the nonhuman. These encounters and the empirical materials they yielded are discussed in relation to the theory of Deleuze, social geographers, and new materialists. Wessel concludes by considering the implications of placed compositional performances as a methodology that can reposition the human to include the nonhuman as agentive participant.
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 | 0.091 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.064 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".