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Record W4410235972 · doi:10.46840/ec.2024.21.736

On the Horizon: a Creative Exploration of Contemporary Trends in Canadian Social Cohesion

2024· article· en· W4410235972 on OpenAlexaffabout
Danielle Nadine Pierre

Bibliographic record

VenueEconomía Creativa · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Sciences and Policies
Canadian institutionsOntario College of Art and Design
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Creativity is performed in ways that are not consistently recognized. This research project explores the intersection of creativity and socio-political contexts by demonstrating creative practices used in strategic foresight and future studies. This exploration reinitiates conversations about social cohesion and suggests that there may be emerging creative economies and new domains for creative professionals to occupy. This study consolidates public conversations between September and December 2024. Signals of change are summarized by nine trends, which are described individually and by a Futures Triangle. Social cohesion is about building group dynamics and meaning between people and their environments. This report provides early insight into possibilities for the future of social cohesion in Canada. To come together in the future, Canadians must consider taking non-partisan and integrative approaches to public administration and collective action, building relationships among citizens, creating awareness of present actions on future generations, adjusting demand for goods and services, and behaving better together. While a more cohesive future is desirable, more can be done to explore how social cohesion is negotiated and constructed. The trends included in this report support such exploration within communities of practice in generative research, collaborative design, future studies, public administration, and governance.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.741
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.087
GPT teacher head0.351
Teacher spread0.264 · 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 designTheoretical or conceptual
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
Published2024
Admission routes2
Has abstractyes

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