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Record W940248834 · doi:10.5206/fpq/2015.1.1

Care, Concern, and Advocacy: Is There a Place for Epistemic Responsibility?

2015· article· en· W940248834 on OpenAlexaffvenue
Lorraine Code

Bibliographic record

VenueFeminist Philosophy Quarterly · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicFeminist Epistemology and Gender Studies
Canadian institutionsYork University
Fundersnot available
KeywordsSituatedEpistemologyPoliticsSociologyPolitical sciencePhilosophyLawComputer science

Abstract

fetched live from OpenAlex

Departing from an epistemological tradition for which knowledge properly achieved must be objective, especially in eschewing affect and/or special interests; and against a backdrop of my thinking about epistemic responsibility, I focus on two situations where care informs and enables good knowing. The implicit purpose of this reclamation of care as epistemically vital is to show emphatically that standard alignments of care with femininity—the female—are simply misguided. Proposing that the efficacy of epistemic practices is often enhanced when would-be knowers care about the outcomes of investigation, I suggest that epistemic responsibility need not be compromised when caring motivates and animates research. Indeed, the background inspiration comes from the thought, integral to feminist and post-colonial theory and practice that, despite often-justified condemnations of research that serves "special interests," particularities do matter, epistemically. Such thoughts, variously articulated, are integral to enacting a shift in epistemology away from formal abstraction and toward engaging with the specificities of real-world, situated knowledge projects. They are not unequivocally benign, for villains too care about the outcomes of their projects. Hence multi-faceted engagements with epistemic practices and processes are urgently required across the social-political world.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.708
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.072
GPT teacher head0.345
Teacher spread0.273 · 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 teacher head, not a consensus.

Study designQualitative
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

Citations46
Published2015
Admission routes2
Has abstractyes

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