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Record W4397009579 · doi:10.3390/cli12050073

People’s Perception of Climate Change Impacts on Subtropical Climatic Region: A Case Study of Upper Indus, Pakistan

2024· article· en· W4397009579 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.

fundA Canadian funder is recorded on the work.
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

VenueClimate · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsnot available
FundersInternational Development Research CentreDepartment for International DevelopmentGovernment of the United Kingdom
KeywordsIndusClimate changeLivelihoodGeographyAgricultureStructural basinSocioeconomicsEnvironmental resource managementEnvironmental protectionEnvironmental scienceEcology

Abstract

fetched live from OpenAlex

In developing countries like Pakistan, the preservation of the environment, as well as people’s economies, agriculture, and way of life, are believed to be hampered by climate change. Understanding how people perceive climate change and its signs is essential for creating a variety of adaptation solutions. In this study, we aim to bridge the gap in current research within this area, which predominantly relies on satellite data, by integrating qualitative assessments of people’s perceptions of climate change, thereby providing valuable ground-based observations of climate variability and its impacts on local communities. Field-based data were collected at different altitudes (upstream (US), midstream (MS), and downstream (DS)) of the Upper Indus Basin using both quantitative and qualitative assessments in 2017. The result shows that these altitudes are highly variable in many contexts: socioeconomic indicators of education, agriculture, income, women empowerment, health, access to basic resources, and livelihood diversifications are highly variable in the Indus Basin. The inhabitants of the Indus Basin perceive the climate changing around them and report impacts of this change as increase in overall temperatures (US 96.9%, MS 97%, DS 93.6%) and erratic rainfall patterns (US 44.1%, MS 73.3%, DS 51.0%) resulting in increased water availability for crops (US 38.6%, MS 39.7%, DS 54.8%) but also increasing number of dry days (US 56.7%, MS 85.5%, DS 67.1%). Communities at these altitudes said that agriculture was their primary source of income, making them particularly vulnerable to the effects of climate change and the dangers that go along with it. The insights are useful for determining what information and actions are required to support local climate-related hazard management in subtropical climate regions. Moreover, it is vital to launch a campaign to raise awareness of potential hazards, as well as to provide training and an early warning system.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.320
Teacher spread0.269 · 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