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Record W2613690700 · doi:10.29173/cais683

Academic Uses of Google Earth and Google Maps in a Library Setting

2013· article· en· W2613690700 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueProceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSI · 2013
Typearticle
Languageen
FieldComputer Science
TopicWeb and Library Services
Canadian institutionsUniversity of TorontoUniversity of Waterloo
Fundersnot available
KeywordsLibrary sciencePolitical sciencePromotion (chess)Academic libraryPresentation (obstetrics)World Wide WebComputer science

Abstract

fetched live from OpenAlex

Over the last several years, Google Earth and Google Maps have become increasingly utilized in academic libraries for promoting and delivering a variety of library services. These have included instructional collaborations with faculty to promoting student engagement across programs and campuses. Seeking to find out exactly how academic libraries were using Google Maps and Google Earth (if at all), the authors launched a online survey in December 2010 to see just what kind of impact the Google mapping products were having in the academic library setting. Receiving over 80 responses from academic librarians and staff from across Canada and the United States, the results showed that over 90% of the respondents use Google Earth and Google Maps for some area of their professional duties in a academic library. These included answering research questions, developing instructional materials for courses, and building tools to promotion and marketing. This presentation will discuss the survey results and summarize the way academic libraries are utilizing Google Earth and Google Maps for instruction, research, and student engagement.Depuis les dernières années, Google Earth et Google Maps sont de plus en plus utilisés en bibliothèque universitaire pour promouvoir et offrir une variété de services en bibliothèque, y compris l’enseignement collaboratif avec les professeurs afin d’accroître l’engagement étudiant, de tous les programmes et campus. Afin de déterminer exactement la mesure dans laquelle les bibliothèques universitaires utilisent Google Maps et Google Earth (le cas échéant), les auteurs ont lancé un sondage en ligne en décembre 2010 pour évaluer l’impact des produits de cartographie de Google dans les bibliothèques universitaires. Plus de 80 sondages ont rempli par des bibliothécaires et du personnel en bibliothèque d’universités au Canada et aux États-Unis. Les résultats démontrent que plus de 90 % des répondants utilisent Google Earth et Google Maps pour certaines de leurs activités professionnelles, y compris répondre à des questions de recherche, développer du matériel pédagogique et élaborer des outils de promotion et de marketing. Cette communication abordera les résultats de la recherche et résumera les modes d’utilisation de Google Earth et de Google Maps dans l’enseignement, la recherche et l’engagement étudiant.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptno category
Domain: not available · Genre: Other
About the Canadian research system: no · About a Canadian topic: no
Not applicablehigh
models agreeAgreement compares identical category sets and study designs across arms.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.036
Open science0.0020.001
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 head0.014
GPT teacher head0.214
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