Map of Countries (2006). United Nations Economic Commission for Europe. Gender Statistics [Archive]: Time Use by Activity | Selection 1: All activities | Selection 2: Both sexes, 2006. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 054-003-066.
Notice bibliographique
Résumé
United Nations Economic Commission for Europe (2015). Gender Statistics [Archive]: Time Use by Activity | Selection 1: All activities | Selection 2: Both sexes, 2006. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. [Data-file]. Dataset-ID: 054-003-066. Dataset: Shows survey data on average amount of time spent on specific activities each day, by sex. The Gender Statistics database presents sex-disaggregated social data for the 56 member states of the United National Economic Commission on Europe (UNECE) region, which include the countries of Europe, but also Canada, the United States, Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, Uzbekistan, and Israel. The data covers the Common Gender Indicators for the UNECE region as well as the data series that are used to calculate these indicators. The data have been supplied by national statistical offices through the network of Gender Statistics Focal Points, and are compiled by the Statistical Division of the UNECE Secretariat from different official national and international sources. Data available varies by country. NOTE: Data-Planet discontinued updating of this dataset in 2011 due to irregularities in the data structure. For more recent data on similar topics, please see the Eurostat database. Time use represents the average time spent (hours and minutes) on an activity per day. All days of the week, as well as working and holiday periods are included. Data refer to employed, unemployed and economically inactive people aged 20-74. Gainful work: includes time spent on main and second jobs (including informal employment) and related activities, breaks and travel during working hours, and on job seeking. Study: includes time spent on study at school and during free time. Domestic work includes housework, child and adult care, gardening and pet care, construction and repairs, shopping and services, and household management. Travel includes commuting and trips connected with all kinds of activities, except travel during working hours. Sleep includes sleep during night or daytime, waiting for sleep, naps, as well as passive lying in bed because of sickness. Meals includes meals, snacks and drinks. Personal care includes dressing, personal hygine, making up, shaving, sexual activities and personal health care. Free time includes all other kinds of activities, e.g, volunteer work and meetings, helping other households, socializing and entertainment, sports and outdoor activities, hobbies and games, reading, watching TV, resting or doing nothing. Category: Population and Income Source: United Nations Economic Commission for Europe The United Nations Economic Commission for Europe (UNECE) was established in 1947 as one of the five regional economic commissions of the United Nations. Its major aim is to promote pan-European economic integration. To do so, UNECE brings together 56 countries located in the European Union, non-EU Western and Eastern Europe, South-East Europe and Commonwealth of Independent States (CIS) and North America. All these countries dialogue and cooperate under the aegis of the UNECE on economic and sectoral issues. http://www.unece.org/ Subject: Time Utilization, Gender
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,007 | 0,036 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,003 | 0,004 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,157 | 0,158 |
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 source (Gemma direct ou Codex distillé), 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 ».