From the Field to the Field: Mapping a Landscape of Qualitative Research Through Scholars’ Personal Letters
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
Despite the growth of qualitative research, we lack a systematic understanding of the lived experiences of qualitative scholars themselves. Our study is motivated by the intuition that by shedding light on the “map makers behind the maps” we may gain a novel view of the field: of the assumptions, emotions, fears and hopes that anchor extant qualitative theorizing. In this spirit, we solicited personal letters from a sample of North American and Western European management and entrepreneurship scholars, inviting them to reflect on their experiences as bases for articulating insights and advice for future researchers. Our letters revealed three distinct “maps of the field”: “roadmaps”; “political maps”; and “pictorial maps.” These maps stressed different features, distinct temporal orientations (past or future), emotions (positive, negative, or mixed), and “navigation advice.” Based on these various “maps” and insights, we draw theoretical and practical implications for future 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.
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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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