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Enregistrement W2526007707

Elderly cyclists´ opinions on safe and joyful cycling

2008· article· en· W2526007707 sur OpenAlexaboutno aff
Lars Ledén, Charlotta Johansson, Peter Rosander

Notice bibliographique

RevueEpubl LTU · 2008
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueUrban Transport and Accessibility
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésCyclingQuarter (Canadian coin)Promotion (chess)TrainKilometerBattery (electricity)Transport engineeringForensic engineeringEngineeringAeronauticsGeographyPolitical scienceCartography
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

A questionnaire was sent to more than 500 elderly (65 years or older) members of the Cycling Promotion in Sweden (Cykelfrämjandet) in June 2007. The foremost reason that elderly ride bicycles is to get exercise, which 94% of the respondents state as a reason. Other often stated reasons are: because it is joyful (84%), because it gives freedom (73%), because it is easy (72%) and because it is easy to park (66%). The foremost reason that the elderly leave their bikes at home and use another means of transportation is bad road conditions during the winter, slipperiness (81%), bad snow removal (79%) and snowfall (77%). Temperatures below zero Celsius restrain about half of the elderly from cycling. Also, long distances are a reason that elderly choose not to use a bike. Some leave their bikes at home when the distance in one direction is more than 6-10 kilometers. Two thirds (65%) of the respondents do not like biking if the (one-way) distance is above 15 kilometers. Almost half of the respondents state that their bike usage would increase if there was a possibility to bring the bike onto busses and trains.The most commonly used equipment is lights, which are used by 81% of the respondents. Most common are battery-powered lights followed by traditional dynamo-operated ones where the generator touches the tire. Some respondents have a dynamo in the hub. The second most common equipment is a helmet, which is used by 80% of the elderly. The remaining fifth does not own one. About two thirds of the respondents use a bicycle-bag or basket and reflectors. Contrary, reflective vests are used only by 17% of the respondents, but in rural areas the usage is close to 50%. Rear-view mirrors are used by a few respondents, but are desired by quite many respondents (28%). Winter tires and winter cycles are desired by one fifth of the respondents. However, more than half of the respondents stated that they do not miss any equipment or that they have no opinion.The most common sites or maneuvers the elderly avoid are roundabouts, left turns and crossing streets without a cycle crossing. Also cycle tracks with moped traffic are avoided by many. The most common reason that the elderly avoid any site or maneuver is that they feel insecure. Many choose to walk their bike, when they perceive something dangerous such as drivers of cars that do not stop or take cyclists into consideration and cars and mopeds that are driven too fast. However 41% of the respondents do not avoid any site or maneuver.According to the elderly, the biggest safety problems are potholes, slipperiness and bad snow removal; 76, 74 and 70% of the respondents have referred to these factors as safety problems. Major problems are also curb stones and cars going too fast. One third of the respondents state that signage and route information for bicyclists is good and another third that it is neither good nor bad.What the elderly say would increase their biking is linked to what they say is important for increased traffic safety. Increased safety would lead to increased biking among the elderly. Requests dealing with the physical design of roads are especially a demand for more and better cycle tracks. Communication between road users expressed as more and better consideration are also perceived to increase their feeling of security and thereby increase their biking.

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)0,001
score de la tête « metaresearch » (Gemma)0,003
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,005
Score d'incertitude au seuil0,009

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0010,000
Science ouverte0,0000,001
Intégrité de la recherche0,0010,000
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

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.

Tête enseignante Opus0,040
Tête enseignante GPT0,315
Écart entre enseignants0,275 · 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.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeQualitatif
Domainenon disponible
GenreEmpirique

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

En bref

Citations1
Publié2008
Routes d'admission1
Résumé présentoui

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