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Record W2125286873 · doi:10.22230/cjc.2002v27n2a1293

Sharpening the Lens: Recent Research on Cultural Policy, Cultural Diversity, and Social Cohesion

2002· article· en· W2125286873 on OpenAlexvenueno aff
Greg Baeker

Bibliographic record

VenueCanadian Journal of Communication · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsnot available
Fundersnot available
KeywordsCohesion (chemistry)Social connectednessRealmSociologyCultural diversityDiversity (politics)ScrutinyPolitical economyPolitical scienceSocial psychologyAestheticsSocial sciencePsychologyLawAnthropology

Abstract

fetched live from OpenAlex

Many of the assumptions surrounding "culture, connectedness, and social cohesion" must be held up to sharper scrutiny, including the nostalgia for a return to simpler times, when cultural consensus and social cohesion seemed easier to achieve. The challenge is not one of "repairing fractured cohesion" or "renewing civil society," but rather of envisioning a new civic realm where diversity is supported by more empirically grounded foundations for claims regarding the interconnections amongst these phenomena. Although we must acknowledge the enormous power of globalizing markets and communications systems, we also need to resist a simplistic equation of these factors with homogenizing cultural trends. Our current discourses related to culture, diversity, and social cohesion require a complete rethinking before we can proceed with policies to respond effectively.

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)0.017
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.954
Threshold uncertainty score0.180

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.024
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0090.014
Science and technology studies0.0100.083
Scholarly communication0.0220.025
Open science0.0030.010
Research integrity0.0070.010
Insufficient payload (model declined to judge)0.0080.000

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 head0.445
GPT teacher head0.405
Teacher spread0.040 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations29
Published2002
Admission routes1
Has abstractyes

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