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Record W1554671493

Assessing a Swedish Social Impact Assessment model for the construction Industry : A Case Study of the Development Project Järvalyftet

2012· book· en· W1554671493 on OpenAlexaboutno aff
Elin Mattsson, Susanna Ternstedt

Bibliographic record

VenueKTH Publication Database DiVA (KTH Royal Institute of Technology) · 2012
Typebook
Languageen
FieldEnvironmental Science
TopicEnvironmental and Social Impact Assessments
Canadian institutionsnot available
Fundersnot available
KeywordsSocial impact assessmentConstruction industrySustainabilitySustainable developmentBusinessFocus (optics)Social impactSocial sustainabilityEnvironmental planningEngineeringPolitical scienceConstruction engineeringSociologyGeography
DOInot available

Abstract

fetched live from OpenAlex

The construction industry has an increased focus on using sustainable methods to reach a more sustainable society but is still lacking the social aspect of sustainability. The belief is that this aspect has to be a natural part in construction projects to successfully plan and develop sustainable societies. A method to achieve this could be the use of Social Impact Assessment (SIA), a method frequently used in other countries such as U.S, Australia and Canada. The aim with the thesis is to investigate how this method can be used in a Swedish context, but also how the public in the best manner can be involved in decisions that affect them. To complement the theory with empirical findings a case study is done within Järvalyftet, one of the biggest redevelopment projects in the Stockholm region at the moment. A SIA deals with several areas and issues and is therefore complex to perform in an efficient way. It is consequently important to create a team with mixed disciplines to be able to manage the work and face the different problems in the best possible way. The thesis indicates that public involvement is of major importance to create an acceptance for the planned project among the affected parties in order to reduce both the timeframe and the costs of the project. Further, the thesis indicates that public involvement early on in a project facilitates for the affected people to deal with changes and trade-offs resulting by the project.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.300
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.002
Research integrity0.0010.001
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 head0.072
GPT teacher head0.378
Teacher spread0.306 · 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 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".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

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