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Record W2871942788 · doi:10.22215/cjers.v11i2.2510

Accommodation of Interests of the State, Business and Civil Society in Environmental Projects Implemented Through Public Private Partnership in the Russian Federation

2017· article· en· W2871942788 on OpenAlex
Andrey Margolin, В. Н. Краснощеков

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe Canadian Journal of European and Russian Studies · 2017
Typearticle
Languageen
FieldEngineering
TopicEngineering and Environmental Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGeneral partnershipAccommodationContext (archaeology)Public–private partnershipCivil societyFinanceState (computer science)Private sectorInvestment (military)BusinessPolitical scienceEconomicsComputer scienceEconomic growth

Abstract

fetched live from OpenAlex

Environmental projects have a number of distinctive features, among them an increased capital/output ratio, relatively high risks, lengthy payback periods, and outcomes that are hard to evaluate using financial indicators. Public private partnership (PPP) appears to be a viable approach for the implementation of such projects; however, existing mechanisms for the accommodation of long-term interest of the state, business and civil society are inadequate to ensure their success. In this context, the author presents an algorithm of multi-criteria analysis to evaluate the social efficiency of PPP-based environmental projects, which takes into account the impact of both financial and non-financial outcomes and includes crowdsourcing public opinion into the final decision-making process. Special priority is given to the assessment of multiplicative effects, as their role and impact on the feasibility of investment are often underestimated. The author’s conclusions and recommendations are illustrated using the case study of a construction project for a municipal solid waste processing facility.
 
 Full text available at: https://doi.org/10.22215/rera.v11i2.1191

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.253
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.051
GPT teacher head0.245
Teacher spread0.195 · 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