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Editorial

2018· article· en· W7022189269 sur OpenAlexaboutno aff

Notice bibliographique

RevueDOAJ (DOAJ: Directory of Open Access Journals) · 2018
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueYouth Education and Societal Dynamics
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésContext (archaeology)Index (typography)AttractivenessGovernment (linguistics)Test (biology)FertilityEconomic JusticeHumanity
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

If you had to choose one moment in history in which to be born, and you didn’t know in advance whether you were going to be male or female, which country you were going to be from, what your status was, you’d choose right now.” This answer to his one-question test was used by Barack Obama in several of his speeches to demonstrate how humanity has made progress up until the present day. Is he right? Beyond asking people what their preferred birth year would be in the context of such a thought experiment, it is possible to compare the attractiveness of actual birth years (and thus epochs in which to lead one’s life) from official statistics. There are already a handful of indices which are, if recorded repeatedly, usable for measuring the changes in quality-of-life circumstances over time, and thus the “position” of succeeding generations in the course of history. Jamie McQuilkin, who is the winner of the 2016/17 Demography Prize, derives an additional index from national statistics in the opening article of this second part of the IGJR double issue on “Measuring Intergenerational Justice for Public Policy”. He combines nine indicators: forest degradation rate, share of low-carbon energy consumption, and carbon footprint in the environmental dimension; adjusted net savings, current account balance, and wealth in equality in the economic dimension; and primary pupil-teacher ratio, fertility rate, and GDP-adjusted child mortality in the social dimension. Unlike other index-builders, McQuilkin takes great pains to lay out all the premises, definitions and data sources of his account in as clear a manner as possible, which makes his article an accessible and instructive read. All-encompassing comparisons of the position of a generation in the “lottery of timing” are nonetheless notoriously difficult to draw. The two subsequent articles confine themselves to public policy. They both treat financial transfers between generations; but a deeper look reveals that their underlying rationale is quite different. Bernhard Hammer, Tanja Istenič and Lili Vargha use a framework of direct reciprocity between generations whereas Paul Kershaw (at least partly) builds upon a concept of indirect reciprocity. This is best explained when we look at the relationship between (familial) generations before the welfare state came into being. The directly reciprocal generational contract is the implicit expectation that parents will care for their children until they are old enough to care for themselves, and children will support their parents, in turn, when their parents can no longer support themselves. Here, the exchange happens between the same generational cohorts but while they are in different age groups. In their work, Hammer, Istenič and Vargha adapt this idea in the context of the welfare state, pinpointing the role of human capital-building and reproduction for the maintenance of generational contracts. The authors develop a new indicator to analyse whether there is a balance between transfers to children and transfers expected by the elderly population in the future. Their results indicate that, in most of the 16 EU countries analysed, the human capital investments in children are far too low to finance the necessary transfers to the elderly population in the future. In the final article, Kershaw writes within a framework of a different logic: indirect reciprocity. Imagine in pre-welfare-state times the members of three generations walking together. The daughter accompanies her mother and her grandmother as they embark on a ritual journey intended to end with the grandmother’s voluntary death. The girl takes pity on her grandmother and convinces her mother to promise to care for the old woman until her natural death in exchange for a promise from the girl to do the same for her mother when the time comes. Here, the exchange does not happen between the same generational cohorts. The creditor generation cannot be paid back by the (then) deceased debtor generation. As the (previous) middle generation has become the debtor generation, the obligation is passed on the next generation (now the middle generation). Kershaw discusses three different approaches in this framework for Canada: the elderly/non-elderly spending ratio; intergenerational reciprocity; and the ability to pay of different age cohorts. Next to calculating some striking results, Kershaw further develops the elderly bias in social spending (EBiSS) as an indicator for the (un)fairness of intergenerational welfare state contracts. For the utility of cross-country comparisons, medical care spending (which is consumed disproportionately in later life) and education (which is consumed earlier) must be taken into account according to Kershaw. Kershaw’s first two stages of analysis are complemented by a discussion about the fairness of the different treatment of generations in welfare states. Since some cohorts are born into favourable eras, and others are not, it is important to examine intergenerational public finances by reference to the standard of living inherited by different age groups, and the socio-economic circumstances they currently face. In response to this, Kershaw in the third stage of his research considers how the standard of living for contemporary seniors compares with that of elderly Canadians four decades earlier; and how the standard of living four decades earlier – when contemporary seniors were young adults – compares with that of young people today. In short, Kershaw suggests that the Canadian government needs to introduce policy changes to readjust the intergenerational imbalances that are negatively affecting younger generations. In the book review section, the first review assesses Birnbaum, Ferrarini, Nelson and Palme’s The Generational Welfare Contract: Justice, Institutions and Outcomes. Again, the focus is on the redistribution of a welfare state’s resources in time. Partly qualifying the “mainstream” thesis that public programmes, such as health care and pensions, are not affordable at their current extent in ageing welfare states, the authors put forward the hypothesis that intergenerational welfare state contracts can lead to positive-sum solutions. In the second book review, Michael Rose’s The Representation of Future Generations in Today’s Democracy, is brought to the attention of the scientific community. The book is written in German but of importance for the debate on specialised agencies for the future. Jörg Tremmel (University of Tübingen) Maria Lenk (FRFG) Antony Mason (IF) Markus Rutsche (University of St. Gallen)

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,014
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Autre · Signal consensuel: aucune
Score de désaccord entre enseignants0,613
Score d'incertitude au seuil0,000

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,014
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0020,001
Études des sciences et des technologies0,0020,001
Communication savante0,0070,004
Science ouverte0,0020,002
Intégrité de la recherche0,0040,005
Charge utile insuffisante (le modèle a refusé de juger)0,3870,235

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,279
Tête enseignante GPT0,616
Écart entre enseignants0,338 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2018
Routes d'admission1
Résumé présentoui

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