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Record W1608081075 · doi:10.55870/tgv.v32i2-3.3538

Jämställdhet, meritokrati och kvalitet - Ett triangeldrama i den akademiska vardagen

2011· article· en· W1608081075 on OpenAlexfundno aff
Kerstin Alnebratt, Birgitta Jordansson

Bibliographic record

VenueTidskrift för genusvetenskap · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsnot available
FundersUniversity of CambridgeInternational Development Research Centre
KeywordsGender equalityPoliticsGender studiesEconomic JusticeSociologyDisciplineConfusionDoing genderPolitical scienceField (mathematics)Social sciencePsychologyLaw

Abstract

fetched live from OpenAlex

In Sweden, the issue of gender equality in higher education and research has been on the agenda since women entered universities in significant numbers more than 40 years ago. Several political initiatives have been taken, which have been crucial to enhanced gender equality but, at the same time, they have been essentially contested in academia itself. In this article we analyse how specific logics, based on the culture of academic research, are hard to reconcile with logics based on political justice that govern the politics of gender equality. Secondly, gender equality is often understood today as concerning knowledge produced by research. Ever since the 1970s, the two lines of development — more women in academia and more gender studies — have been intertwined in Swedish research policy. Support for female-dominated research fields like gender studies has been perceived as supporting gender equality in higher education. Gender studies have, in many ways, benefited from this support but, at the same time, reduced the field to being a matter of gender equality, rather than a research area in its own right. Consequently, gender studies in Sweden have been challenged from other disciplinary perspectives by those who claim that they represent not research, but a political endeavor to bring about gender equality. Without a clear distinction between methods of improving conditions both for women researchers and for gender research, the two will be conflated. This confusion is problematic not only for women involved in gender research but for the field itself. Supporting gender studies may be dismissed as political and incompatible with academic doxa and self-understanding. On the other hand, favoring women in the name of gender equality is incompatible with the understanding of fairness, which forms the meritocratic order in academia.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.630
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.002

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 head0.223
GPT teacher head0.313
Teacher spread0.090 · 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
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

Citations5
Published2011
Admission routes1
Has abstractyes

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