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Record W7095462262

Social Inequalities – Youth Opportunities

2015· article· en· W7095462262 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicIntergenerational and Educational Inequality Studies
Canadian institutionsnot available
Fundersnot available
KeywordsInequalityEliteSocial inequalityQuarter (Canadian coin)Social exclusionSocial changeSocial classField (mathematics)Social group
DOInot available

Abstract

fetched live from OpenAlex

One of the most oft-debated subjects today is the structural changes within education. There are passionate debates about whether young people's inequalities of opportunity have increased or decreased. One view is that the system has become more open during the restructuring, while others argue that the changes that took place in the 1990s led to a more “elite-centric ” system. One group emphasizes the diversity and multifaceted nature of the system, while another points to a deep division within, namely, the growing exclusion of the children of uneducated rural social groups from the system of education. Adherents of one view see the inevitability of the creation of a market-compatible system of schooling, while others point out the destructive effects of the market on equality of opportunity. Those arguing for a market-compatible education—especially in the field of higher education—emphasize that different social groups make conscious choices as to where and in what direction they want to take their careers. The other side argues, however, that social selection was never as strong in Hungary as in the 1990s. This claim is substantiated with data that show that 80 % of students in elite institutions of higher education (arts and sciences, medical school) come from about one quarter of all high schools. The Two Scenarios and Social Inequalities

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.797
Threshold uncertainty score0.750

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.665
GPT teacher head0.448
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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