MétaCan
Menu
Back to cohort
Record W1506449029

Re-Visioning Implementation of Brownfields Through a Network Lens

2011· article· en· W1506449029 on OpenAlexaboutno aff
Ellen Rogers

Bibliographic record

VenueSSRN Electronic Journal · 2011
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsnot available
Fundersnot available
KeywordsAgency (philosophy)CraftBrownfieldContext (archaeology)Public relationsNexus (standard)BusinessPort (circuit theory)Environmental planningSuperfundPolitical scienceEngineeringSociologyRedevelopmentCivil engineeringHazardous wasteGeography
DOInot available

Abstract

fetched live from OpenAlex

Brownfields, with roots in Superfund, bring unique challenges to local communities in how they are to be implemented. Especially for smaller communities, brownfields sites can be paralyzing as they lack the resources and the market advantages of larger communities to attract private investments. Yet, the struggles of these communities are real and continuing. Further insight into the circumstances under which the administrators of these programs make their implementation decisions and craft their approaches to cooperation and participation can enable this understanding. This research seeks to begin an exploration of which factors matter to administrators as they make these decisions by examining the Port of Vancouver and the Port of Bellingham and their brownfield programs. This research will explore the role of site context, agency resources and community resources in influencing the decisions of public administrators as they make cooperation decisions. This research suggests that agency and community factors may have stronger influences than site context.

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)0.014
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.110
Threshold uncertainty score0.218

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0120.029
Scholarly communication0.0160.012
Open science0.0020.010
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0070.000

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 head0.106
GPT teacher head0.437
Teacher spread0.331 · 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 designQualitative
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
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueSSRN Electronic JournalSame topicCommunity Health and DevelopmentFrench-language works237,207