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Enregistrement W6923798299 · doi:10.15139/s3/nozyud

Relocation and Romantic Relationships - Longitudinal, 2019-2022

2022· dataset· en· W6923798299 sur OpenAlexaffabout

Notice bibliographique

RevueUNC Dataverse · 2022
Typedataset
Langueen
DomainePsychology
ThématiqueIdentity, Memory, and Therapy
Établissements canadiensUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésRelocationAttritionRomanceService (business)Sample (material)

Résumé

récupéré en direct d'OpenAlex

We obtained a sample of 455 participants (i.e., 227 couples and 1 individual) who relocated to a different city, state/province, or country, with one partner who initiated the couple’s move (i.e., relocaters, who typically moved for career opportunities), and the other partner who accommodated their partner’s initiation to move (i.e., trailers). Couples moved an average of 2,702 kilometers (range: 18km to 15,535km), with some moving to a different city (23.6%), most moving to a different province/state (46%), and others moving internationally (29.8%). Participants filled out a baseline survey ~2 months before couples moved, 5 shorter bi-weekly surveys in the wake of the move, and follow-up surveys at 3, 6, 9, and 12 months post-move. Attrition was relatively low but increased over time (Ns: 1st bi-weekly = 423, 2nd bi-weekly = 406, 3rd bi-weekly = 400, 4th bi-weekly = 395, 5th bi-weekly = 384, 3mo follow-up = 365, 6mo follow-up = 347, 9mo follow-up = 326, 12mo follow-up = 288). Some attrition is due to couples that broke up over the course of the study (N = 38, 8.3%). Participants were recruited via a wide variety of ways, such as through moving service companies, relocation offices of large companies, universities, and hospitals, and various online networking sites (e.g., kijiji, Craigslist, Reddit, Facebook groups). Couples were eligible when both partners spoke English, were over the age of 18, were in a romantic relationship, currently lived together, and importantly, when they were going to relocate with their partner in at least two months, which was primarily for one of the partners (e.g., to support their career opportunities). Interested couples were enrolled after they had a phone call with a research team member to confirm their eligibility and explain the study procedure. Each participant received $10 CAD for the baseline survey, $7 CAD for each bi-weekly survey (5 bi-weekly surveys X $7 CAD = $35 CAD), and $15 CAD for each follow-up survey (4 follow-up surveys X $15 CAD = $60 CAD). Participants also received a bonus of $15 CAD if they completed all of the study surveys or all but one of the study surveys. In total, participants could receive up to $120 CAD ($240 CAD per couple), or the equivalent in another currency. Participants ranged in age from 18 to 54 (M = 29.8, SD = 5.8), 51% identified as women, 46.6% as men, 2% as non-binary, 0.2% as transgender, and 0.2% as agender. The majority identified as heterosexual (80%), with others identifying as bisexual (7.9%), lesbian (3.3%), queer (2.2%), asexual (2.2%), gay (1.8%), pansexual (1.8%), or “other” (e.g., androsexual; 0.9%). Most participants identified as White (North American/European, 62.9%) and others identified as East Asian (8.8%), South Asian (8.1%), Black (7.5%), Latin American (4.2%), bi- or multi-ethnic (e.g., White/Black, 4.6%), Native American/First Nations (0.7%), or “other” (e.g., Middle Eastern, South-East Asian, 3.3%). All participants were living together with their partner and were in their current relationship for 6.26 (SD = 4.98) years on average. Most participants were married (47.5%) or engaged (9.2%), while others indicated they were dating (27.5%), common-law (14.3%), or “other” (e.g., domestic partnership, 1.5%). About a quarter of the participants had children (23.1%), with most of these having one (13.4%) or two (8.4%) children. This project was approved by the University of Toronto research ethics board on December 14, 2018 (#00036971).

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Jeu de données · Signal consensuel: Jeu de données
Score de désaccord entre enseignants0,143
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
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 savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,1490,006

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 Opus0,046
Tête enseignante GPT0,313
Écart entre enseignants0,267 · 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeSans objet
Domainenon disponible
GenreJeu de données

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
Publié2022
Routes d'admission2
Résumé présentoui

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