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When RateMyProfessor Meets the #MeToo Movement: Bottom-up Bullying in Academia

2020· article· en· W3131604958 on OpenAlex
Ruth McKay, Bill Irwin, Randy Appel

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.

Bibliographic record

VenueInternational Journal for Digital Society · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicWorkplace Violence and Bullying
Canadian institutionsCarleton University
Fundersnot available
KeywordsMovement (music)PsychologyArtAesthetics

Abstract

fetched live from OpenAlex

The #MeToo and Time's Up movements have created increased awareness around inappropriate work behaviour. According to these two partially overlapping movements, some organizations have been permissive in enabling employees to misuse their positions to assert undue power over others. Managers also recognize that complaint processes may be inadequate in resolving these issues. This paper uses a #MeToo lens to investigate student bullying, mobbing, and sexual harassment enabled through RateMyProfessor.com (RMP). For this research RMP is used as a proxy for social media sites that are visible and curtained to public viewing. It also considers how the need for the academy to operate as a hyper-commercialized business may be contributing to the silence of universities on the misuse of sites such as RMP. Main research questions include the following. Why is harassment of faculty through social media sites such as RMP permitted and even valued? How do social media sites' content and audience differ from university evaluations of faculty?

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.431
Threshold uncertainty score0.901

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.053
GPT teacher head0.358
Teacher spread0.306 · 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