Concept mapping internal validity: A case of misconceived mapping?
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
Since the early 1990s, the concept mapping technique developed by William M. K. Trochim has been widely used by evaluators for program development and evaluation and proven to be an invaluable tool for evaluators and program planners. The technique combines qualitative and statistical analysis and is designed to help identify and prioritize the components, dimensions, and particularities of a given reality. The aim of this paper is to propose an alternative way of conducting the statistical analysis to make the technique even more useful and the results easier to interpret. We posit that some methodological choices made at the inception stage of the technique were ill informed, producing maps of participants' points-of-view that were not optimal representations of their reality. Such a depiction resulted from the statistical analysis process by which multidimensional scaling (MDS) is being applied on the similarity matrix, followed by a hierarchical cluster analysis (HCA) on the Euclidian distances between statements as plotted on the resulting two-dimensional MDS map. As an alternative, we suggest that HCA should be performed first and MDS second, rather than the reverse. To support this proposal, we present three levels of argument: 1) a logical argument backed up by expert opinions on this issue; 2) statistical evidence of the superiority of our proposed approach and 3) the results of a social validation experiment.
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 | 0.010 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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