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Record W4307053258 · doi:10.1002/ev.20514

Identity as a compass when navigating uncharted equitable spaces: Our queer evaluation practices

2022· article· en· W4307053258 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.

Bibliographic record

VenueNew Directions for Evaluation · 2022
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsUniversity of SaskatchewanSaskatchewan Health
Fundersnot available
KeywordsQueerDialogicSituatedSociologyNormativeIdentity (music)EpistemologyNorm (philosophy)Social psychologyPsychologyComputer scienceAestheticsGender studiesPedagogy

Abstract

fetched live from OpenAlex

Abstract Alternative approaches within evaluation increasingly allow space for evaluators to bring themselves to their work. As queers, we are gifted‐partially as a necessity for our survival‐with deeper understandings of and navigational capacities to work within complexity. Furthermore, existing as queer empowers us to think and operate outside what is the norm, known, familiar and comfortable, and thus enables us to challenge normative systems for purposes of social change. Our chapter offers situated insight into what queer evaluation practices look like and empowers us to practice bringing ourselves into different contexts, including uncharted spaces. We illustrate principles of queer evaluation through cases of our unique identities, contexts, landscapes, and evaluation experiences, within a process that is iterative, dialogic, and relational. We argue that the exploration of ourselves is critical as evaluators and invite readers to wander alongside us while actively searching their identities. Rather than hiding these biases and perspectives, we believe in the importance of knowing oneself and our connections to the histories of those who came before, which serve as our guides. Only from this point can we begin to unravel the unknown into the known and transform the inequitable into the equitable that has yet to exist. We argue that by embracing our identities we are better able to navigate the complexities that exist in our work and deepen our understanding of the contexts around us.

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)0.051
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.614
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0510.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0030.000
Scholarly communication0.0010.004
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0200.001

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 head0.379
GPT teacher head0.585
Teacher spread0.205 · 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