Technique Triangulation for Validation in Directed Content Analysis
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
Division of labor in wedding planning varies for first-time marriages, with three types of couples—traditional, transitional, and egalitarian—identified, but nothing is known about wedding planning for remarrying individuals. Using semistructured interviews, the author interviewed 14 couples in which at least one person had remarried and used directed content analysis to investigate the extent to which the aforementioned typology could be transferred to this different context. In this paper she describes how a triangulation of analytic techniques provided validation for couple classifications and also helped with moving beyond “blind spots” in data analysis. Analytic approaches were the constant comparative technique, rank order comparison, and visual representation of coding, using MAXQDA 2007's tool called TextPortraits.
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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 | 0.043 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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