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Record W2239173202

A critical definition of the concept of public space

2014· article· en· W2239173202 on OpenAlexaboutno aff
Sarah Isabella Chiodi

Bibliographic record

VenuePORTO Publications Open Repository TOrino (Politecnico di Torino) · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse academic and cultural studies
Canadian institutionsnot available
Fundersnot available
KeywordsSpace (punctuation)Public spaceSocialitySociologyIdentification (biology)Quarter (Canadian coin)Public relationsMedia studiesEpistemologyGeographyPolitical scienceComputer scienceArchitectural engineeringEngineeringArchaeology
DOInot available

Abstract

fetched live from OpenAlex

What do we mean when we talk about public space? We asked some privileged testimonials during the research programme of relevant national interest (PRIN 2009) titled: "Public spaces, mobile populations and processes of urban reorganisation". Among the questions in the in-depth interview on relations between urban populations and public space, we asked for a definition of public space and the identification of some significant spaces in the city of Turin, in the City Centre and the San Salvario district and the quarter of Barriera di Milano closer the outskirts of the city. The definition of the concept of "public space" highlighted certain significant aspects. One of these concerns a sort of standardisation among the various affirmations, that identify public space as an, albeit, weak space for socialisation, to which certain thoughts on the role of commerce and new media are linked. Another emerging and opposing aspect emphasizes a clear difference between the different views, which depends largely on the professional and cultural experiences of each interlocutor. In summary are recognized some different approaches: public space as a relational space, "cappuccino" space, weak sociality space, new relational spaces and a new type of public space: the "District Houses". Photos of Turin public spaces and interview passages are reported

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)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: none
Teacher disagreement score0.911
Threshold uncertainty score0.638

Codex and Gemma teacher scores by category

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

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 head0.081
GPT teacher head0.270
Teacher spread0.189 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2014
Admission routes1
Has abstractyes

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