Metaphor-Themed Studies in Social Studies Education in Turkey and Their Evaluations in Terms of Conceptual Metaphor Theory (CMT)
Bibliographic record
Abstract
The aim of the present study is to examine postgraduate theses and published articles on "analysis of metaphorically used words in discourse" in the field of social studies education in Turkey by document analysis method. Within the scope of the research, The National Thesis Center and Dergipark databases were surveyed. The survey revealed 22 completed theses and 39 published articles between the years of 2010 and 2022. First, the studies were analysed in terms of the study/publication year of the works, the universities where they were conducted, their sample/study groups, the methodological framework they were based on, their data collection tool, the expertise of the researchers and thesis advisors, and the metaphors that were the subject of the research. The works were subsequently evaluated in terms of CMT (Conceptual Metaphor Theory) and were subjected to five research questions. This evaluation revealed that the studies examined: (i) do not establish a relationship between their research findings and the theoretical framework of CMT although they view metaphors as products of conceptual thinking; (ii) do not benefit adequately from the essential references or seminal works of CMT; (iii) do not align themselves with a particular theory of metaphor or an approach, and, therefore, lack criteria for how they associate metaphor with thought; (iv) do not make explicit the criteria according to which they classified the statement of participants as metaphorical; and (v) try to reach the data suited to their research purpose with a data collection tool coded as "A is X like or as B", which is a coding scheme that is conventionally identified as a simile rather than a conceptual metaphor among CMT adherents.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".