From Mussels Stand to Becoming a Doctor: A Discussion on the Importance of Education in the Vertical Transition Between Social Strata in Terms of Career Choices and Sources of Vocational Awareness in Children with Low Socioeconomic Level
Bibliographic record
Abstract
This study aims to discuss the importance of education in vertical transition between social strata in the context of career choices and vocational awareness sources in children with low socioeconomic level. The study used a phenomenological design within a qualitative research approach framework. The study group consisted of 55 fourth-grade students enrolled in a primary school in a low socioeconomic area of Izmir province in Turkey. Findings of the research laid out that the students mostly wanted to be a doctor, their positive attitudes towards the profession and their desire to be beneficial to the society gained importance in their career choices, taking the example of people who they encountered in real life and who they watched on TV affected their career choices, and that there were participant views indicating that a thorough presentation of careers was not conducted even though a number of professions were mentioned in the lesson. The findings were discussed in terms of carrying out vocational guidance more carefully for participants consisting of children with low socioeconomic level who have parents with low education level so that its disadvantages can be eliminated.
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 | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.013 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| 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 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".