MétaCan
Menu
Back to cohort
Record W2947420321

Experiences of natural climate variability in Newfoundland and Labrador

2018· dissertation· en· W2947420321 on OpenAlexfundaboutno aff
Olivia Vilá

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2018
Typedissertation
Languageen
FieldSocial Sciences
TopicClimate Change Communication and Perception
Canadian institutionsnot available
FundersMarine Environmental Observation Prediction and Response Network
KeywordsClimate changeGeographyBaseline (sea)Climate stateClimatologyPerceptionNatural (archaeology)Climatic variabilityEnvironmental resource managementEnvironmental scienceGlobal warmingEffects of global warmingPsychologyPolitical scienceEcology
DOInot available

Abstract

fetched live from OpenAlex

Climate variability is the semi-regular fluctuation of climate about its mean state. Whereas there is considerable research into how daily variability and long-term change may influence attitudes and perceptions of climate change, the influence of climate variability acting over timescales between these extremes (i.e. interannual anomalies, decadal cycles) has mostly been neglected in human dimensions of climate research. This lack of consideration of long-term climate variability has limited our capacity to assess climate perceptions effectively and holistically. The goal of this research was to explore the extent to which individuals notice, interpret, and communicate climate variability. Through semi-structured, one-on-one interviews with people living in areas experiencing considerable climate variability, this research has begun to develop a baseline understanding of the weather and climate phenomena that are prevalent in participants’ lives. This project also analyzes some of the language strategies that individuals use to communicate weather/climate cycles and other relevant climate phenomena. Subsequent focus group discussions were used to test tools for communicating important weather/climate phenomena. Because human values and cultural meanings are often removed from climate science, climate-related information is difficult to understand and contextualize when disseminated to the public. By focusing on the social aspects of weather and climate experiences, this research identifies the climate features that matter most to individuals in the community being researched. The results of this project can inform future research investigating perceptions and experiences of past weather and climate phenomena. Furthermore, because longer-term variability is often misrepresented as counter-evidence to anthropogenic climate change by either those who do not understand or care to understand the phenomena, the results of this research can begin to aid in reducing the potential misinterpretations between natural climate variability and climate change.

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)0.002
metaresearch head score (Gemma)0.002
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: Qualitative
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.119
Threshold uncertainty score0.240

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.006
Scholarly communication0.0030.002
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.118
GPT teacher head0.378
Teacher spread0.260 · 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
GenreOther

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
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueMemorial University Research Repository (Memorial University)Same topicClimate Change Communication and PerceptionFrench-language works237,207