Intergenerational Bonding in Family and School Contexts: Which Does Impact More on Degree Aspiration of Students?
Bibliographic record
Abstract
Among the factors which have trajectory roles on the academic attainment of students, intergenerational bonding is the foremost of them. Though intergenerational bonding has basically focused on parent-child relationship, contemporary studies further consider the teacher-student relationship as intergenerational bonding to identify its effect on the academic attainment of students. In this study, we first examine both types of bonding which are created by parent-child and teacher-student relationships and how these impact on the degree of aspiration of secondary school students. Then, we compare these effects to identify which factor affects more on the degree aspiration outcome of students. We use the data collected from 553 students of Grade IX from 12 secondary schools in Bangladesh. The effect size of parent-child bonding and teacher-student bonding are compared using standardized Beta (β) weights of these two variables. The results show that beyond the socioeconomic status, both parent-child bonding and teacher-student bonding significantly and positively impact on students' degree aspiration outcome. Furthermore, when we compared the effect size of these two variables, results show that parent-child bonding had more strength compared to teacher-student bonding to predict the degree aspiration outcome of students.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".