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Record W3216863802 · doi:10.14288/1.0343079

An Investigation into Security in Single-Stall Washrooms

2017· article· en· W3216863802 on OpenAlexaff
Andrew Dombowsky, Eric Cauri, Anthony Bilinski, Rishabh Chaudhary

Bibliographic record

VenuecIRcle (University of British Columbia) · 2017
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsStall (fluid mechanics)Computer securityComputer scienceEngineering

Abstract

fetched live from OpenAlex

The purpose of this report is to explore the best possible methods of decreasing misuse and vandalism in UBC’s single-stall washrooms. This research was prompted by UBC Access and Diversity’s concerns regarding the recent trend of students using single-stall washrooms, mainly the ones located in Koerner Library, as private study rooms. This issue creates problems for other users as a legitimate user may be unable to access proper washroom facilities when needed, should any in the vicinity be taken up by students abusing the space. The conclusions found in this report will also pertain to the limitation of vandalism in UBC’s washroom facilities, although this issue is secondary to the concerns in regards to misuse and therefore research was performed primarily with misuse as the main focus. The proposed solutions are to be simple to implement, relatively inexpensive and in particular will not limit accessibility for any potential users. Therefore this report will be targeting as wide a demographic as possible, including both students and non-students. Three main methods of deterrence were found to be most effective. The first is signage employing positive wording to encourage users to limit their time spent in the washroom and not to vandalise. The second is room lighting tied to a timer set off upon entrance into the washroom. The third is signage indicating clearly the phone numbers and other descriptive information as to who to contact to report vandalism. It was found that due to their incredibly simple premise and their excellent cost to effectiveness ratio, the addition of descriptive signage with positive wording placed in UBC’s single-stall washroom facilities will serve as the absolute best deterrent to misuse and vandalism. Disclaimer: “UBC SEEDS provides students with the opportunity to share the findings of their studies, as well as their opinions, conclusions and recommendations with the UBC community. The reader should bear in mind that this is a student project/report and is not an official document of UBC. Furthermore readers should bear in mind that these reports may not reflect the current status of activities at UBC. We urge you to contact the research persons mentioned in a report or the SEEDS Coordinator about the current status of the subject matter of a project/report.”

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)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0030.004
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.002

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 head0.011
GPT teacher head0.178
Teacher spread0.168 · 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 designObservational
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

Citations1
Published2017
Admission routes1
Has abstractyes

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