Camp methodologies: The “how” of studying camps
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
Abstract This special section contributes to the growing interdisciplinary field of camp studies by examining the ways in which scholars methodologically approach and study camps and camp‐like spaces. The characteristics of camps, which render them of interest to scholarship in the first place, simultaneously generate methodological, ethical, and practical questions for research. Yet comparatively few studies have explicitly addressed the methods and methodologies in camp research. How do camp contexts shape our underlying research philosophies and how do particular ways of doing research impact our conceptualisations of camps? The contributors to this special section provide a variety of answers to these questions, drawing on empirical research in/on current and historical camp settings. Overall, we gesture towards “camp methodologies” not as a set of prescribed tools, techniques, or epistemologies to be followed when studying camps but as a shorthand for approaches that consider first, how camp geographies delimit research activities and second, how methodological choices in turn (re)construct the camp conceptually in different ways. Ultimately, this collection aims to encourage critical debates and reflections to shed more light on the methodological effects, positionalities, responsibilities, complicities, and continuing necessities of studying camps.
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 | 0.025 | 0.010 |
| 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 | 0.001 |
| 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