YOUTH’S FUTURE ORIENTATION AND WELL-BEING: MATERIALISM AND CONCERNS WITH EDUCATION AND CAREER AMONG TURKISH AND NORWEGIAN YOUTH
Bibliographic record
Abstract
Youths’ well-being and subjectivity are strongly related to prevailing political, economic, and social conditions. Neoliberalism has extensively permeated societies worldwide, changing the way individuals, especially youth, make sense of their surroundings and themselves. There is thus an increasing need to investigate how youth subjectivities are influenced in contemporary societies that are under the influence of neoliberalism. Through an analysis of the future orientation of youth, we can investigate discourses that shape youth subjectivities. In this study, we perform a Foucauldian discourse analysis of the future orientation of youth — high school students, from two national contexts, Turkey and Norway — who were asked to write an essay on their personal futures. We investigate what dominant discourses are revealed in the youths’ writings and how they may influence their subjectivities and well-being. We detail two frameworks of discourses, one pertaining to materialism and the other pertaining to education and career, that our participants drew upon in their writings. We relate these discourses to neoliberalism and discuss the extent to which youth constitute themselves as neoliberal subjects of their respective societies. We discuss how these discourses may also be related to their well-being in diverse ways.
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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 | 0.005 | 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 | 0.006 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".