Bibliographic record
Abstract
No accessJournal of Human SecurityOther Journal Article01 January 2010Learning from Canada: Russian Basin Management of Transboundary Rivers Authors: Alina Nikolaevna Porokh Authors: Alina Nikolaevna Porokh Associate Professor, International Relations, Regional Studies and Political Science, Volgograd State University, email: [email protected] Google Scholar More articles by this author SectionsAboutPDF/EPUBExport CitationsAdd to FavouriteAdd to FavouriteCreate a New ListNameCancelCreate ToolsTrack CitationsCreate Clip ShareFacebookTwitterLinkedInEmail Abstract After the USSR's disintegration, many rivers received international status. This provided the basis for developing a reliable mechanism of regulation of relations between the states on transboundary river exploitation. Three basic problems associated with the example of transboundary rivers of Russia and Kazakhstan are: the unsatisfactory ecological state of international rivers; the necessity of changing the priorities concerning protection and resource conservation of water; the basin approach based on integrated water resource management of the whole international rivers basin as a unified ecosystem. For the basin management system to be improved in Russia, it is important to study the international experience and the Canadian one, in particular. Previous article Next article RelatedDetails View PUBLICATION DETAILSDate of Publication:January 2010Journal:Journal of Human SecurityISSN:1835-3800Volume:6Issue:3Page Range:61-68First Page:61Last Page:68Source:Journal of Human Security, Vol. 6, No. 3, 2010: 61-68Date Last Modified:05 September 2018 12:24Date Last Revised:23 April 2012 Original DOI: 10.3316/JHS0603061IdentifierTransboundary RiverGeographic LocationRussia (Federation)RussiaSubjectWatershed managementWater resources developmentWater conservation--ManagementRiversWater--Pollution METRICS Downloaded 0 times Copyright© Human Security Institute, 2010Download PDFLoading ...
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".