Young people not in education, employment or training (NEET), UK, Aug 2016
Notice bibliographique
Résumé
Estimates of young people (aged 16 to 24) who are not in education, employment or training, by age and sex.The percentage of all young people in the UK who were NEET was 11.7%, down 0.3 percentage points from January to March 2016 and down 0.9 percentage points from a year earlier.Just under half (46%) of all young people in the UK who were NEET were looking for work and available for work and therefore classified as unemployed.The remainder were either not looking for work and/or not available for work and therefore classified as economically inactive. In this bulletinThis statistical bulletin contains estimates for young people not in education, employment or training (NEET) in the UK.An is available on our website.The bulletin is published 4 times article providing background information a year in February, May, August and November.All estimates discussed in this statistical bulletin are for the UK and are seasonally adjusted.The figures discussed in this statistical bulletin are obtained from the Labour Force Survey (a survey of households) and are therefore estimates, not precise figures.This statistical bulletin is accompanied by a in Excel spreadsheet format.data table Definition of young people not in education, employment or training (NEET) Young peopleFor this release, young people are defined as those aged 16 to 24.Estimates are also produced for the age groups 16 to 17 and 18 to 24 and broken down by sex.For April to June 2016, there were 62,000 people aged 16 to 17 who were NEET, up 5,000 from January to March 2016 and up 11,000 from a year earlier.There were 781,000 people aged 18 to 24 who were NEET, down 27,000 from January to March 2016 and down 89,000 from a year earlier. Unemployed young people who were NEETUnemployment measures people without a job who have been actively seeking work within the last 4 weeks and are available to start work in the next 2 weeks.For April to June 2016, there were 390,000 unemployed young people (aged 16 to 24) who were not in education, employment or training (NEET), up 9,000 from January to March 2016 and down 41,000 from a year earlier.For April to June 2016
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 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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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 ».