Guidelines for reporting research using systematic coding of observed human behaviour (SCOBe)
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 Systematic coding of observed human behaviour (SCOBe) is used across disciplines and topics but methodological reporting is often incomplete. We developed internationally generated, interdisciplinary guidelines for methodological reporting of such research. Using Delphi methodology, a working group of 22 experts sought group consensus in three rounds. Participants first assessed an initial set of reporting criteria (round 1). Next, in interactive meetings participants revised these criteria and reached consensus on reporting content (rounds 2 & 3). We present 20 criteria constituting the first comprehensive reporting guidelines for SCOBe research using existing, newly developed, or modified coding systems. The criteria encompass three procedural domains: 1. Research context; 2. Properties of the coding scheme; and 3. Application of the coding scheme. The presented guidelines will assist in substantiating and assessing the quality of SCOBe research. We encourage researchers to adopt these guidelines, to enhance quality of mono- and interdisciplinary 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 | 0.105 | 0.062 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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