MétaCan
Menu
Retour à la cohorte
Enregistrement W2150271140

Interpretive collaborative review: enabling multi-perspectival dialogues to generate collaborative assignments of relevance to information resources in a dedicated problem domain

2008· article· en· W2150271140 sur OpenAlex

Pourquoi ce travail est dans la base

Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.

affAu moins un auteur déclare une institution canadienne dans l'instantané OpenAlex épinglé.

Notice bibliographique

RevueElpub digital library · 2008
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueKnowledge Management and Sharing
Établissements canadiensUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésRelevance (law)Context (archaeology)DeliberationComputer scienceProcess (computing)Task (project management)Online discussionKnowledge managementMeaning (existential)Data sciencePsychologyWorld Wide WebEngineering
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

<p>Interpretive Collaborative Review (ICR) is a process designed to assemble electronically accessible research papers and other forms of information into collaboratively interpreted guides to information artefacts relevant to particular problems. The purpose of ICR is to enable collective understanding of a selected problem area that can be developed and represented by evaluating (reviewing) selected artefacts through a collaborative deliberation process. ICR has been conceptually formalized as an online environment enabling collaborative evaluation of relevancy relationships articulated in the triad of: 1) specific problems (topic), 2) diverse stakeholders and reviewer perspectives (context), and 3) particular settings where the problem matters (task). We define relevance as a cognitive recognition of proximal meaning relationships among the triad nodes of topic, task, and context. Three necessary dimensions of relevance relationships are proposed: 1) precedence, 2) validity, and 3) maturity. Based on experience with other forms of collaborative knowledge construction such as structured dialogue and cooperative learning, we conceptualized the ICR process as encompassing three phases: 1) discovery, promoting initial interpretations and definition, 2) deliberation, promoting emerging understanding and acceptance of degrees of interpretation within the group and 3) dissemination, promoting summation, validation, and distribution or publication of conclusions. The ICR method starts by recruiting a community of reviewers with necessarily diverse perspectives who agree to collaborate in identifying and evaluating information artefacts that can inform knowledge construction centered on a problem of common interest. A discovery phase allows reviewers to declare perspectives that are further delimited and explored collaboratively through the use of group dialogue around challenge questions. This is followed by a deliberative phase that facilitates collaborative dialogue aimed at developing a shared understanding of available information artefacts and their significance and of how those sources are relevant to the problem context. A final dissemination phase involves recording and publishing the knowledge synthesis and innovation that emerged from this collaborative dialogical process to affect knowledge transfer. Alignment of perspectives is promoted through collaborative generation of an aggregated report that describes the perceived relevancy relationships for each knowledge artefact evaluated in the review collection. While useful by itself, this report also serves as the raw material for a new form of scholarly publication, the 3D-Review, where relevancy relationships are used to guide suggested actions that could be taken with respect to advancing knowledge of the problem and options for addressing it. Both reports and reviews are indexable and electronically accessible, allowing other communities or individuals to find, retrieve, and act upon the new knowledge associated with the reports and reviews. This process of rigorous and purposeful deliberation enabled through online support of honest dialogue has the potential to develop into a new form of scholarly activity that should be useful in integrative scholarship.</p>

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.

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)0,001
Version: codex-gemma-dda1882f352aStatut 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 enseignants0,788
Score d'incertitude au seuil0,706

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,003
Études des sciences et des technologies0,0000,000
Communication savante0,0000,005
Science ouverte0,0000,000
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 Opus0,016
Tête enseignante GPT0,262
Écart entre enseignants0,246 · 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