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Record W7024179550

Review Of "The Economic Implications Of Social Cohesion" Edited By L. Osberg

2003· article· en· W7024179550 on OpenAlexaboutno aff

Bibliographic record

VenueWorks - Scholarship, Research, & Creative Expression (Swarthmore College) · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Capital and Networks
Canadian institutionsnot available
Fundersnot available
KeywordsCohesion (chemistry)Social entropySocial capitalSocial changeSocial mobilitySocial philosophySocial positionSocial economy
DOInot available

Abstract

fetched live from OpenAlex

Tackling a topic of growing interest to social scientists, this volume offers theoretical and empirical insights into the relationship between social capital and social cohesion and a series of social and economic variables. These range from the specific (e.g., the relationship between social cohesion and the well-being of children and, in another chapter, the complex pathways relating health and social cohesion) to the more general (e.g., the ways in which social cohesion mediates the relationship between the public and voluntary sectors or how they affect regional development) to, finally, the macroeconomic implications of social cohesion. Editor Osberg (Dalhousie Univ., Canada) is explicit in noting that this volume does not offer a single answer to the question of how social capital and social cohesion affect economic and social outcomes--nor does it offer a common explicit understanding of what social cohesion and social capital are. Nevertheless, the book incorporates thought-provoking attempts to define these terms and to map their relationships to fundamental aspects of modern society and economy and can serve as a good introduction to this area of study for those readers already equipped with some background in economics and social policy. Summing Up: Recommended. Upper-division undergraduate through professional collections.

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)0.006
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.416
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0030.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.056
GPT teacher head0.391
Teacher spread0.335 · 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
Published2003
Admission routes1
Has abstractyes

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