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Record W7034714977

Working towards improved climate change communication in the Riding Mountain Biosphere Reserve

2002· dissertation· en· W7034714977 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2002
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicSolar and Space Plasma Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsClimate changeContext (archaeology)BiospherePolitical economy of climate changeEffects of global warmingGlobal warmingQualitative researchEcological forecasting
DOInot available

Abstract

fetched live from OpenAlex

This thesis is a synthesis of a research project that explored the issue of climate change communication in the Riding Mountain Biosphere Reserve (RMBR). Climate change has become an increasingly important environmental issue that has gained wide public awareness over the past fifteen years. Yet, despite the overwhelming multi-disciplinary research, policy efforts, and public education and communications on the issue, there has not been appreciable improvement in public understanding of the potential impacts of climate change and actions that can be taken. There is also a shortage of evaluative research conducted to determine the attributes of effective communications with adult learners. This study identified perspectives on the climate change issue among selected adult learners; developed and evaluated a climate change information program; established the effectiveness of the program in communicating climate change information with adults; identified potential barriers to communication; and, suggested tools and methods for improved communication of climate change information with adult learners. This research was carried out in a case study setting using a community climate change workshop. An extensive literature review conducted prior to the study helped set the context for the investigation. An adaptive multi-criteria process of evaluating the workshop program was implemented, primarily based on a comparative analysis of participants' perspectives on the climate change issue and workshop activities. A presurvey, a post-survey, researcher observation, and semi-structured follow-up interviews were the instruments used to collect the qualitative and quantitative data. The perspectives of participants show a high concern for local environmental and socioeconomic issues. Regarding the climate change issue, there was a high level of awareness, moderate level of knowledge, and low level of understanding prior to the workshop. As a result of the workshop activities, there were varying levels of improved understanding on climate change. In general, this occurred most often as a result of workshop information that was locally and personally relevant in terms of the potential biophysical, and socio-economic impacts of climate change and what could be done about them. The communication qualities that were associated with improved understanding, and therefore deemed to be more effective, were personal and interactive in nature, integrative of participant's views, engaging, and interesting. Specifically, expert verbal and interactive presentations, and the climate change short story were found to be the most effective workshop tools. Conversely, The Winds of Change poster and govemmental materials were least effective for workshop participants. In conducting future climate change communications, stakeholders' perspectives should be considered, and existing organizations identified to coordinate and deliver the climate change message through several tools and methods. As well, the barriers to future communications need to be further identified and addressed. More resources need to be allocated towards environmental education in the RMBR and in Canada as a whole that includes a strong climate change component and leads towards more environmentally responsible behavior amongst the general adult population

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)0.010
metaresearch head score (Gemma)0.009
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 score0.992
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.002
Scholarly communication0.0050.004
Open science0.0020.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.026
GPT teacher head0.226
Teacher spread0.200 · 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
Published2002
Admission routes1
Has abstractyes

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