MétaCan
Menu
Back to cohort
Record W2593911022

Future of Nostalgia: How might we use nostalgia to improve psychological resilience in a fast-changing world?

2016· other· en· W2593911022 on OpenAlexaff
George Wang

Bibliographic record

VenueOCAD University Open Research Repository (OCAD University) · 2016
Typeother
Languageen
FieldPsychology
TopicNostalgia and Consumer Behavior
Canadian institutionsOntario College of Art and Design
Fundersnot available
KeywordsSocial connectednessFeelingResilience (materials science)AestheticsPsychological resilienceModernization theorySociologyPsychologySocial psychologyPolitical scienceArt
DOInot available

Abstract

fetched live from OpenAlex

Nostalgia as a longing for home, where we feel a deeper sense of connectedness and a slower sense of time. Today’s heightened nostalgia is due to modernization, which created an environment where people are lonelier and more pressed for time– which have significant implications for well-being -- than people living in societies that are not as affluent or have not adopted the modern way of living. As the characteristics of modern society persist into the future, there will be increasing need to foster resilience among people. Nostalgia is a vehicle that can be used in experience design to transport positive feelings from the past into the present and improve psychological resilience. Deliverables include heuristics for leveraging nostalgia in experience design and a workshop guide that facilitates the design of nostalgic experiences.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.019
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0030.004
Scholarly communication0.0060.010
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0190.003

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 head0.050
GPT teacher head0.345
Teacher spread0.295 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations1
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueOCAD University Open Research Repository (OCAD University)Same topicNostalgia and Consumer BehaviorFrench-language works237,207