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
Institutional ethnography (IE) is an innovative approach to research that requires a significant shift in researchers’ ordinary habits of thinking. There is a growing body of methodological resources for IE researchers however advice about how to proceed with analysis remains somewhat scattered and cryptic. The purpose of the first of a two-paper series is to contribute to publications focused exclusively on analysis. The aim is to provide practical tips to support researchers to shift their ordinary habits of thinking. This first paper outlines how this must happen at the outset of the research design. Analysis of the phenomenon under study commences as the research is being formulated. The approaches to analytical thinking outlined in this paper are based on my own IE research and also my experience working with graduate students since 2008. In this first volume of the two-paper set I provide a brief background to the method and direct readers to important IE resources. I outline three core methodological concepts: standpoint, problematic and ruling relations. I discuss how these concepts guide the early analytical thinking that is embedded in the research design and the critical analysis of the literature that is part of the process of analysis in IE. The second paper provides practical advice for working with data.
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 | 0.104 | 0.052 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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