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Record W7134293235

Women, Transgender, Femme and Nonconforming People

2019· report· en· W7134293235 on OpenAlexaboutno aff
Kate Davis, Lucie Stepanik, Sydney Rankmore, Kaithlyn Given

Bibliographic record

VenuecIRcle (University of British Columbia) · 2019
Typereport
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsIncentiveNightlifeQualitative researchEvent (particle physics)Set (abstract data type)OutreachPsychological intervention
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this research is to explore the barriers and incentives that exist for women, transgender, femme and gender nonconforming people to participate in nighttime events on UBC campus. Through our research, we hoped to be able to understand in what spaces women, transgender, femme and gender nonconforming people want to see more events taking place, what would compel them to attend nighttime events on campus, and what is currently preventing them for participating in existing nighttime events. To answer these questions, we used a mixed-method qualitative approach. We started with a review of key literature on the subjects of gender, nightlife and inclusive spaces. This helped us understand what other Canadian campuses are doing to create inclusive campus events and also to frame our research through an intersectional feminist lens. We then collected our data through three outreach and engagement activities. We set up a booth at the NEST Building in central UBC campus with two large engagement boards, asking “where do you want to see a nighttime event on campus?” and “what would draw you to a nighttime event on campus?”. We approached groups of people passing by, and asked them to participate. Participants were asked to write their identifiers on sticky notes and place them on the two boards. If respondents were willing to participate further, we would conduct a short and informal interview that allowed us to gather more detailed information about barriers and incentives to participating in nighttime events on campus. Our last engagement method was in the form of a short online survey that we sent to three groups on campus that work to promote gender-diversity and inclusion at UBC. In our research we found that just over 50% of respondents wanted to see nighttime events in and around the NEST. The next most-desired location was in the Arts and Culture District of UBC campus. For type of events, those involving food, music, and drinking were most popular among our studied population. Accessible transportation has been identified as a main draw to nighttime events, specifically for those living off-campus, making up 60% of respondents. We found that many people attend events for social interaction or because their friends are also attending. Music is also a main draw to nighttime events; however, it can also be a deterrent to individuals if it they do not enjoy the type of music being played. Further, transportation, along with distance from home are the primary factors preventing our targeted population from attending nighttime events. Cost, food and busy schedules were also identified as being important factors. These findings have led us to make four key recommendations. First, event information should be shared and contained in a central location. Second, events should be free as often as possible. Third, events should be held in central locations, close to main transportation stops on campus and fourth, events on campus should have a greater diversity of content to attract a wider range of students. 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)0.004
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.972
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.008
Scholarly communication0.0050.004
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.024
GPT teacher head0.207
Teacher spread0.183 · 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 designNot applicable
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
Published2019
Admission routes1
Has abstractyes

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