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Record W2736555827

Pathological gambling. Chinese community in Southern Italy

2011· article· en· W2736555827 on OpenAlexfundno aff
Gioacchino Lavanco, Floriana Romano, Cinzia Novara, Marcela Croce, Cedric Messina, Lauren Arcuri

Bibliographic record

VenueIRIS UniPA (University of Palermo) · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsnot available
FundersCentre for Interdisciplinary Research in Rehabilitation
KeywordsPathologicalGeographyMedicinePathology
DOInot available

Abstract

fetched live from OpenAlex

If the global, demographic and economic change we are witnessing is requiring a new perception of civil society, the role of CP is to initiate and maintain dialogue and mutual support with all actors interested in social change and social innovation.Therefore, CP, among others should start to be a real "linking science" by Discovering empowerment patterns between individuals, groups and social structures not only in the neighborhood, but in all kind of settings where people work and life together (companies, virtual communities, social policy), Learning not only from the past, but sense emerging futures by learning across generations, cultures and institutions Establishing new intersectoral alliances and test new forms of collaboration between different actors in society Enabling mutual risk taking through experimental settings and program evaluation.This requires to add to "incremental", step-by-step social innovations forms of profound, more "radical" social innovations for which collaboration with other disciplines and actors are needed (see the works of C. Otto Scharmer (2007) or the concept of "design thinking" (Brown 2009). Perspectives for Community Psychology in EuropeTraditional values of CP like social change and transformation and current challenges today require more than working in a local community and/or improving the social situation of specific groups.While this work will remain an important core part of CP, the field should empower itself use its competencies to develop social innovations and look at emerging futures by developing shared goals (and take shared risks) by collaborating with other disciplines, companies or other actors in society.CP as a field in Europe should focus on macro-and micro-issues of community building together with various partners: this is why it is important to develop close ties not only with national community psychology groups in Europe and other parts of the world, but also with other psychological and social science/social action networks and associations.The European Union and the European Commission will be one of the most important partners to foster community building and a sense of community in our society.To support this movement and to strengthen the capabilities of each community psychologist in Europe, we should form Community Interest Groups (professional, student and practitioner groups) which will be able to maintain, and promote the rich body of knowledge on community building and develop future questions which may be important for our society.We should invest in a joint education and practice in community psychology and CP special topics in order to develop the idea of community psychology for young professionals.For this we can use and institutionalize a rich body of experience of community psychology programs in universities and schools all over Europe.The time of an interdisciplinary community building and social innovation master program should come within the next years.These kind of programs could enhance the skills for the future of community psychology in Europe:In Social Skills students and practitioners will experience the art of community building as a collaborative and empowering background, leading to social responsiveness and inclusion Community Psychology: Common Values, Diverse Practices 13 Design Skills will develop both strategic-innovative and creative abilities in order to nurture mutual knowing, awareness and playfulness, and Action Skills will focus on how to co-create, implement and evaluate new concepts and social innovations to build communities in different settings.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.161
Threshold uncertainty score0.320

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.093
GPT teacher head0.280
Teacher spread0.187 · 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 designObservational
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".

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Citations0
Published2011
Admission routes1
Has abstractno

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