<b>Research Note</b>—How Semantics and Pragmatics Interact in Understanding Conceptual Models
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
Underlying the design of any information system is an explicit or implicit conceptual model of the domain that the system supports. Because of the importance of such models, researchers and practitioners have long focused on how best to construct them. Past research on constructing conceptual models has generally focused on their semantics (their meaning), to discover how to convey meaning more clearly and completely, or their pragmatics (the importance of context in model creation and use), to discover how best to create or use a model in a given situation. We join these literatures by showing how semantics and pragmatics interact. Specifically, we carried out an experiment to examine how the importance of clear semantics in conceptual models—operationalized in terms of ontological clarity—varies depending on the pragmatics of readers' knowledge of the domain shown in the model. Our results show that the benefit of ontological clarity on understanding is concave downward (follows an inverted-U) as a function of readers' prior domain knowledge. The benefit is greatest when readers have moderate knowledge of the domain shown in the model. When readers have high or low domain knowledge, ontological clarity has no apparent benefit. Our study extends the theory of ontological clarity and emphasizes the need to construct conceptual models with readers' knowledge in mind.
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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 | 0.010 | 0.001 |
| 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 | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| 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