Are precariousness and temporality the main characteristics of the youth employment in Spain
Notice bibliographique
Résumé
In Spain the rate of youth unemployment has exponentially increased in the past few years, and it has turned into a structural problem. When the fourth quarter of 2014 ended, the destruction of employment, which begun along with the economic and financial crisis in 2008, has specially affected young people so that, among the people under the age of 30, the number of unemployed people was 1.495.600, 645.000 more than in the first quarter of 2008. Nevertheless, before 2008, the youth unemployment rate was already reaching 17,4% and some studies were alerting of the vulnerability of the above mentioned group of people, especially in the following areas: labour, education, residential and reproductive. Moreover, in this period of time, the employment policy has been affected, with no doubt, by the labour reform of 2012 (RDL3 / 2012 and Law 3/2012), by introducing new rules on the mediation in the labour market (Article 16.3 the Workers' Statute (ET)), the vocational training and new contractual modalities, specially modifying the ?contract for training and learning? (Article 11 ET), the modification of the part-time contract (Article 12 ET) and the distance contract (formerly called ?working at home contract?, Article 13 ET) and the introduction of a new indefinite contract called 'support to entrepreneurs'. These reforms have gone in the opposite direction to strengthen employment policies aimed to achieve the right to work or full employment for young people, law and constitutional mandate that in times of crisis are likely to disappear or be completely isolated. Labour statistics are one of the indicators that best express the economic and social reality of a country. Through the ?Muestra Contínua de Vidas Laborales? (MCVL) 2013, the career path between 2008 and 2013 of young people under 30 years is analysed, in order to determine changes and characteristics of their connection to the labour market. The research work shows that, between 2008 and 2013, most of the contracts signed with young people under 35 years were temporary and low paid. At the end of 2014, 78% of this group worked in the private sector, 46% with temporary contracts of which 36.6% for ?labour and service?, one in five young people did it part-time and one in ten with a temporary part-time contract. With micro data from the EPA, related to the fourth quarter of 2014, it is observed through two Logit models, how a low level of education and the sector of activity increase the likelihood that a young person under 34 years on the one hand, becomes unemployed and secondly, occupied by a temporary contract.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».