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Record W191944147

Urban Environmental Education and Sense of Place.

2013· dissertation· en· W191944147 on OpenAlexfundno aff
Alexey V. Kudryavtsev

Bibliographic record

VenueeCommons (Cornell University) · 2013
Typedissertation
Languageen
FieldSocial Sciences
TopicIndigenous and Place-Based Education
Canadian institutionsnot available
FundersUniversity of WaterlooU.S. Environmental Protection Agency
KeywordsSense of placePlace attachmentPlace-based educationSense (electronics)Environmental educationPlace identityGeographyAging in placeEnvironmental planningEnvironmental ethicsSociologyUrban planningPedagogyPsychologySocial scienceSocial psychologyEngineeringCivil engineeringGerontologyMedicinePhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Urban environmental educators are trying to connect students to the urban environment and nature, and thus develop a certain sense of place. To do so, educators involve students in environmental stewardship, monitoring, activism, and outdoor recreation in cities. At the same time, sense of place has been linked to pro-environmental behaviors and other desired educational outcomes. However, the related literature from environmental psychology has rarely been applied to environmental education research, particularly in cities. In this dissertation, I apply the sense of place framework to environmental education, and explore the development of sense of place among high school students in seven afterschool and summer urban environmental education programs in the Bronx, New York City. First, I reviewed the academic literature on urban environmental education in the United States to better understand educational programs in the Bronx. I found that urban environmental education programs may pursue several goals, and one of them is teaching about cities as social-ecological systems in which both social and natural components are essential. Second, I reviewed the literature on sense of place, including its role in environmental education. I conceptualized the idea of ecological place meaning, i.e., viewing environmental and nature-related phenomena as symbols or valued elements of places. Third, in 2010, I explored the impact of urban environmental education on sense of place among students. I conducted pre/post surveys with 87 urban high school students (mean age = 16), including 64 students in 6-week urban environmental programs (experimental group), and 23 students in nonenvironmental, summer youth employment programs (control group). Results showed that urban environmental education programs significantly strengthened ecological place meaning but did not influence place attachment among experimental students; no changes were found in the control group. Fourth, I collected and interpreted nine educators' and five students' narrative profiles to explore the reasons for and approaches to developing ecological place meaning in the city. The narrative analysis showed that educators are trying to cultivate ecological place meaning among students to help them understand and appreciate urban nature and places, and imagine how the urban environment could be improved. Narratives also demonstrated that ecological place meaning is nurtured among students through direct experiences of urban places, social interactions with educators and environmentalists, and the development of students' ecological identity. This dissertation raises questions about how nature-related phenomena in cities-including wetlands and terrestrial ecosystems, green infrastructure, and nature-related outdoor activities such as environmental stewardship and outdoor recreation-are valued by urban residents. Urban environmental education strengthens students' appreciation of the urban environment and nature, and experiences in these programs themselves become part of students' ecological place meaning.

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)0.001
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0030.002
Open science0.0000.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.012
GPT teacher head0.204
Teacher spread0.192 · 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
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

Citations11
Published2013
Admission routes1
Has abstractyes

Explore more

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