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Record W4247534511 · doi:10.1515/9783839443767-006

5. Present and Future of Gender in Impact Assessment: a Standpoint—a Paradigm Shift?

2018· book-chapter· en· W4247534511 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venuetranscript Verlag eBooks · 2018
Typebook-chapter
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsParadigm shiftPsychologyEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

Present and Future of Gender in ImpactAssessment: a Standpoint-a Paradigm Shift?It is said that "theories are to serve a purpose of change, or none." 1 Accordingly, the overall paradigm of my study is feminist: I propose that an implementation of gender equality tools for policy IA will eventually contribute to better equality policy and programming outcomes.Mainstreaming GIA/GBA practices in public policy and programme analysis is indispensable both to fulfilling constitutional and international commitments to legal equality as well as to exercising democratic stewardship.In the first part of this last chapter, I synthesise my empirical findings, providing comparative conclusions from the Canadian and European approaches to gender analysis.In the second part, I then contextualize these empirical results in relation to feminist, post-positivist, standpoint and critical governance theories.In the third and concluding part, I present a vision for the future of IA and the role of gender analysis could play in it. 2 gendeR eQuaLity goveRnance thRough iMpact assessMent: coMpaRative concLusionsThis section provides a comparative overview of the implementation and practice of gender analysis tools in the Canadian and European environments.It identifies the factors that hinder enhanced tool implementation and practice and those that drive change by providing institutional learning opportunities.The following table is a reminder of the genealogy of each tool.

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)0.003
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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.769
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0120.000

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 head0.151
GPT teacher head0.434
Teacher spread0.282 · 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