Portraiture as Pedagogy
Bibliographic record
Abstract
In this reflective essay, five members of a research team involving graduate students and a faculty member offer individual "studies" of specific moments in the field in which lessons about methodology, the research context, and the researcher herself/himself crystallized. The article highlights the pedagogical possibilities of portraiture for introducing graduate students to qualitative research methodology. Each "study" illuminates how different kinds of boundaries are negotiated: whether it is the boundaries of access to a research site; the boundaries of personal or professional recognition; the boundaries of the body and physical space; the boundaries of racial identification; or the boundaries of the interior and exterior selves. These are not lessons that can be taught/learned within the constraints of a classroom, whether a lecture hall or the most progressive seminar. It is in the actual experience of negotiating these boundaries that the intricacies of the research process manifest, and in the process, the inquiry itself grows and moves through the necessary explorations that are the heart of qualitative research.
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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.010 | 0.052 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".