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Record W4256414661 · doi:10.24036/perspektif.v3i3.285

[no title]

2020· article· W4256414661 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJurnal Perspektif · 2020
Typearticle
Language
FieldEngineering
TopicWetland Management and Conservation
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

This study intends to analyze a program using the SWOT Analysis method (strengths, weaknesses, opportunities and threats) in the disaster resilient Nagari program. The disaster resilient village program aims to provide an understanding to the community about disaster risk reduction and selfrescue efforts before the program is implemented. The type of research that I use is qualitative research with descriptive methods. Data collected by interview and documentation study, interview guides in the form of questions that have been prepared, the data collection tools that the authors use are cameras, cellphones, and recording devices. The selection of informants was carried out by means of purposive sampling. The instrument used was the researcher himself, for the validity of the data the author did so by means of source triagulation. From the results of the study it can be concluded that the strengths of this program are adequate human resources, the weakness of this program is the limited funds / budget that causes the program can not run optimally, the opportunities of this program the use of ecotourism as disaster risk reduction, threats from the program this is the low level of community knowledge in responding to the condition of the South Pesisir District which is prone to disasters.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.424
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0000.001
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 head0.024
GPT teacher head0.204
Teacher spread0.180 · 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