MétaCan
Menu
Back to cohort
Record W2165104234 · doi:10.1057/ejis.2012.1

The benefits and dangers of enjoyment with social networking websites

2012· article· en· W2165104234 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEuropean Journal of Information Systems · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsLakehead University
Fundersnot available
KeywordsHabitAddictionArtifact (error)Set (abstract data type)PhenomenonPsychologyStrategic information systemDual (grammatical number)Social psychologyComputer scienceInternet privacyKnowledge managementInformation systemManagement information systemsEpistemologyEngineering

Abstract

fetched live from OpenAlex

Information Systems enjoyment has been identified as a desirable phenomenon, because it can drive various aspects of system use. In this study, we argue that it can also be a key ingredient in the formation of adverse outcomes, such as technology-related addictions, through the positive reinforcement it generates. We rely on several theoretical mechanisms and, consistent with previous studies, suggest that enjoyment can lead to presumably positive outcomes, such as high engagement. Nevertheless, it can also facilitate the development of a strong habit and reinforce it until it becomes a ‘bad habit’, that can help forming a strong pathological and maladaptive psychological dependency on the use of the IT artifact (i.e., technology addiction). We test and validate this dual effect of enjoyment, with a data set of 194 social networking website users analyzed with SEM techniques. The potential duality of MIS constructs and other implications for research and practice are discussed.

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.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.690
Threshold uncertainty score0.347

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.021
GPT teacher head0.252
Teacher spread0.231 · 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