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Record W4410705098 · doi:10.29173/cais1878

Supported Yet Isolated

2025· article· fr· W4410705098 on OpenAlexvenueno aff
Mary Moen, Lauren H. Mandel

Bibliographic record

VenueProceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSI · 2025
Typearticle
Languagefr
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental science

Abstract

fetched live from OpenAlex

This paper explores graduate students’ experiences and perceptions of using discussion forums to build a sense of community in an accelerated online Master of Library and Information Studies program. The Classroom Community Short Form survey was adapted to include short answer questions. The results suggest that while students feel supported and that they care about each other, they still feel isolated. Discussion forums that were informal, provide peer to peer interaction and participation by the instructor were more likely to create a sense of community. Supportés mais isolés : Perspectives d'étudiants diplômés sur la construction de communauté par le biais de discussions dans les forums dans le contexte d'un programme de MBSI en ligne RésuméCet article explore les expériences et les perceptions des étudiants diplômés par rapport à l'utilisation de forums de discussion pour bâtir un sentiment de communauté dans un programme en ligne accéléré de maîtrise en bibliothéconomie et sciences de l'information. Le court sondage sur la communauté de classe a été adapté pour y inclure des questions à réponse courte. Les résultats suggèrent que bien que les étudiants se sentent supportés et qu'ils se soucient les uns des autres, ils se sentent tout de même isolés. Les forums de discussion qui étaient informels, qui apportaient des interactions entre les pairs et dans lesquels les formateurs participaients, avaient plus de chances de créer un sentiment de communauté.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.808
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0020.005
Open science0.0030.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.285
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSISame topicService-Learning and Community EngagementFrench-language works237,207