MétaCan
Menu
Back to cohort
Record W7101147745

Intergenerational Solidarity: Setting the parameters for Tomorrow's Society in Europe

2016· article· en· W7101147745 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicDiscrimination and Equality Law
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)AlienationHomosexualityAbortionInstitutionOrder (exchange)DoctrineSocial issues
DOInot available

Abstract

fetched live from OpenAlex

Policies made by national and EU bodies almost always reflect the perspectives of politicians and advisers, rather than those of the young, which are often markedly different. Every EU institution needs to try harder to capture the hearts and minds of the young in order to arrest their growing alienation from politics. One of the most striking features of the difference in attitudes between the older and the younger in much of Europe is in their attitude to religion — and arguably even more importantly — to sensitive social issues. On these, younger citizens tend to be very much more liberal than their elders. Opinion polls in the UK show clearly that less than a quarter of young people regard themselves as religious. Only one in 14 of younger people think that the Catholic Church should “protect the sanctity of human life by campaigning, for example against abortion and euthanasia”. And a much higher proportion of the young than the old want contraception to be widely available, are liberal on the question of homosexuality and are pro-choice over abortion. Indeed only about 10 % of Catholics support their Church's doctrine on contraception, homosexuality and abortion. And only 4 % of Catholics under 40 years old think that there should

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 imitation

Not 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.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.009
Scholarly communication0.0100.008
Open science0.0010.013
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0080.001

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 head0.248
GPT teacher head0.429
Teacher spread0.182 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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
Published2016
Admission routes1
Has abstractyes

Explore more

Same topicDiscrimination and Equality LawFrench-language works237,207