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Enregistrement W4403423576 · doi:10.1145/3677053

PACMHCI V8, CHI PLAY, October 2024 Editorial

2024· article· en· W4403423576 sur OpenAlexaff
Regan L. Mandryk, Alena Denisova, Julian Frommel, Kathrin Gerling

Notice bibliographique

RevueProceedings of the ACM on Human-Computer Interaction · 2024
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueDigital Games and Media
Établissements canadiensUniversity of Victoria
Organismes subventionnairesnon disponible
Mots-clésHistory

Résumé

récupéré en direct d'OpenAlex

We are excited to present PACM HCI's 2024 issue on games and play research, which contains 63 original and highly relevant articles covering the entire spectrum of HCI games research. As in the previous year, we used three recommendations ' 'Accept with Minor Revisions', 'Revise and Resubmit', and 'Reject.' For papers that were accepted with minor revisions, the second round of reviews was a 'light-touch' process in which the editorial board members checked the revisions, whereas papers that received Revise and Resubmit received another full round of external reviews with the same reviewers in most cases, and were also subjected to a final selection process. This second revision was treated as a real resubmission, which meant that it was given full consideration, but no guarantee or preferential treatment towards acceptance; a share of the revised papers was ultimately rejected. We would like to acknowledge the efforts that our community has made in adapting to this new process, working together with the submitting authors to achieve high-quality scholarship. The track editorial board consisted of 32 members and a total of 230 external reviewers from around the world ensured a high-quality review process. After the first round of submissions, each paper was handled by a primary track editorial board member who received reviews from a second track editorial board member and two external reviewers so that each submission received at least three high-quality reviews. After reviews were completed and checked for quality, the primary initiated discussion amongst the reviewers and came up with a preliminary recommendation (accept, between accept and revise and resubmit, revise and resubmit, between revise and resubmit and reject, reject). Papers that were in the middle three categories were then discussed in two synchronous virtual track editorial board meetings that took place over two consecutive days. The inclusion of the board meeting at this stage was a new addition to the review process last year. We included it to better calibrate decision making across the committee at this critical point in the review process, ensure consistency in outcomes, promote reflection and consideration at this stage in the process, and mentor newer editorial board members in the review process. We strove for a diverse program approaching games research from a variety of perspectives, including design, engineering, psychology, computer and data science while at the same time only accepting high-quality pieces of work. In this issue, we observe the following distribution of primary contributions: 42.9% of papers self-classify as using qualitative methods, 11.1% use quantitative methods, and 20.6% use mixed methods. Additionally, 3.2% of papers present design artifacts and 6.3% present technical artifacts. Finally, 4.8% of papers employ meta-research methods, 6.3% of papers present a new methodological approach, and 4.8% of papers contribute to the development and validation of theory. All articles in this issue were invited to present at the ACM CHI PLAY 2024 conference. We thank our dedicated team of track editorial board members, external reviewers, and paper authors, who continue to support the new review process and timeline, contributing to the maturation and growth of the PACM HCI games and play research community, and resulting in this issue of 63 exciting and highly relevant articles. This issue's 63 papers reflect the importance of play in our everyday lives, comment on recent trends and technical developments relevant to games and play, and also represent a significant effort of our community in coming together to produce a collection of research that highlights the multifaceted value of play.

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)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,508
Score d'incertitude au seuil0,556

Scores Codex et Gemma par catégorie

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

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 Opus0,039
Tête enseignante GPT0,352
Écart entre enseignants0,312 · 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 tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
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

Citations0
Publié2024
Routes d'admission1
Résumé présentoui

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