Impact of Number and Type of Figures’ Identification on Accessing Caricatures’ Meaning
Bibliographic record
Abstract
The present paper is part of an MA thesis; it aims at quantitatively and qualitatively analyzing the objective of the study which reads: examining the impact of the number and type (strip or comprehensive) of figures’ identification on accessing caricatures’ meaning. The first part of the objective is quantitatively analyzed using EXCEL software whereas the second part of the objective is analyzed qualitatively using Tolman’s Theory of MENTAL MAPS (1948). The study ends up with a number of results, such as the percentages of comprehensive thinking or identification are higher than that of the strip way of identification. As a result, the study concludes that there are many factors that affect image reading where both the number of the figures identified and type of thinking are cases in point. However, it has been noticed that the full identification of figures is important, but what is more important is to know which of these figures need to be comprehensively conceptualized, and the sequence by which such figures are mapped and linked.
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.
How this classification was reachedexpand
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 | 0.000 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".