MétaCan
Menu
Back to cohort
Record W3013616591 · doi:10.15273/pnsis.v50i2.9999

Responding to the Call for Climate Action

2020· article· en· W3013616591 on OpenAlexaffvenue
Daniel E. Lane

Bibliographic record

VenueProceedings of the Nova Scotian Institute of Science · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change, Adaptation, Migration
Canadian institutionsUniversity of OttawaUniversité Sainte-Anne
Fundersnot available
KeywordsPolitical economy of climate changeClimate changeSustainabilityBusinessVulnerability (computing)Political scienceMainstreamEnvironmental resource managementClimate justicePublic relationsEnvironmental planningEconomicsGeographyEcology

Abstract

fetched live from OpenAlex

Global calls for action on climate change have become more urgent in recent years. However, how to act to achieve climate sustainability remains elusive. The evidence is clear that governmental initiatives – global, national, and provincial – have not been able to coalesce into a meaningful strategy for climate sustainability. What is required is a shift in climate responsibility from governments to individuals and communities who think globally but are best able to act locally. To encourage the citizenry to act requires a science-based information and education whereby climate action is clearly defined along with the consequences of actions (or inaction). Education must include a climate curriculum as a mainstream subject in our schools. Using this approach, local community baselines of climate information, vulnerability, and adaptive capacity can be established. In enhancing their climate roles, governments’ need to shift from carrying out mandates for climate response, to becoming auditors of carbon use in which citizens and businesses are given incentives to reduce carbon footprints. Finally, increased investments need to be directed to communities so that they can take more responsibility and be more prepared to live with climate change impacts. Governments also need to engage the community in participatory strategic long-term planning for adaptation to the changing climate. Keywords: climate action, climate responsibility, institutional arrangements, science-based information, education legacy, strategic planning, community investment

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 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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.421
Threshold uncertainty score0.852

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.206
GPT teacher head0.369
Teacher spread0.163 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the Nova Scotian Institute of ScienceSame topicClimate Change, Adaptation, MigrationFrench-language works237,207