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Record W7018177956

COVID-19 Student Interviews - Armstrong, Abrea

2020· other· en· W7018177956 on OpenAlexaboutno aff

Bibliographic record

VenueWakeSpace Scholarship (Wake Forest University) · 2020
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsDowntownPrideLeagueSpace (punctuation)Quarter (Canadian coin)Economic JusticeEthos
DOInot available

Abstract

fetched live from OpenAlex

Abrea Armstrong is the Marketing is the Marketing and Communications Manager for the Innovation Quarter, a space in Winston-Salem that houses businesses and organizations and is aimed at promoting new ideas and creativity. She has also recently become the President of the Winston-Salem Young Professionals, a branch of the Winston-Salem Urban League which was created to promote personal, professional, and social growth in young people and to give them opportunities to serve their local community. In this interview, Armstrong discusses her experience working with the Innovation Quarter and living in downtown Winston-Salem during the COVID-19 pandemic, emphasizing how her time management skills have benefited her during this time. She describes how Winston-Salem has become quieter and how that absence of people has provided the perfect opportunity for protests and marches, since there was less activity to interrupt. She shares how she believes that the "we're all in this together" messaging around COVID-19 has contributed to this wave of the Black Lives Matter movement and speaks about her role in that movement. She explains the push to abolish the police and shares that she views progress as the goal, taking pride in small steps towards justice and abolition.

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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.063
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.004
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0040.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0130.027

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 head0.044
GPT teacher head0.293
Teacher spread0.250 · 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; both teacher heads agree on what is shown here.

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
Published2020
Admission routes1
Has abstractyes

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