“Teacher” from the Children’s Perspective: A Study by Metaphors
Bibliographic record
Abstract
<p>The purpose of this study is to determine the perception of teachers by 10 year-old primary school childrens by the metaphors they developed. The sample covers totally 441 children [224 females (50.8%) and 217 males (49.2%)] living in Izmir, Turkey. Participants were asked to complete the prompt “Teacher is like…, because…’’. In identifying their perceptions, the qualitative research model (Holloway &amp; Wheeler, 2002) was utilized, which contributes to the investigation of the individual’s perceptions, feelings, and experiences within the framework of Phenomenological design. At the end of the research female students produced 52 metaphors, and males did 44 for teacher images. However, 7 metaphors were commonly created by both genders. They were categorized in 8 conceptual themes. The children’s perceptions of “teacher” were clustered especially in the conceptual theme of Family Member (25%) and Warm-hearted Person (8%), with emotional and relational feelings which can be explained by the children’s attachment relations (Sabol &amp; Pianta, 2012), that are similar for their families and their teachers. Gender was found to be significantly related with the images of teachers.</p>
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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 | 0.000 |
| 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) | 0.002 | 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".