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Record W325942702

Between a Flake and a Strident Bitch: Making 'IT' Count in the Academy. (Articles)

2000· article· en· W325942702 on OpenAlexvenueno aff
Pamela Moss, Martha McMahon

Bibliographic record

VenueResources for feminist research · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Research Methods and Ethics
Canadian institutionsnot available
Fundersnot available
KeywordsSociologyContext (archaeology)PoliticsSilenceMedia studiesAestheticsPower (physics)MainstreamEmbodied cognitionEpistemologyLawHistoryArtPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

In this paper, we address issues of (ac)countability in the context of reflexively critiquing how feminist qualitative research is conventionally understood within the mainstream academy. The concrete examples we give may be from different individuals' experiences, or from a composite of experiences; they may be fictional truths or perhaps even creative non-fiction. Our goal is analytical, to show how social processes work with regard to making qualitative work count in the academy. As actors in a play, cast as somewhere between a flake and a strident bitch, our characters in this paper take on experiences rather than have them. Our tale dramatizes the workings of power/knowledge/space regimes, as embodied in the experiences of the characters who talk and walk through this text. Listening to you, I sometimes envy the way you can articulate your experience. I find it so hard to articulate mine. It has been subtly unspeakable: beyond the capacity of my speech. Often I am reduced to silence or I babble, pointing to but not being able to put words on what is going on. How can I separate my politics from my/self? And why is it that when I try to communicate what it is I am thinking, I'm reduced to a personality type, some psychological disorder, or dehumanized in a way that creates a formidable chasm between the other speaker and me. I am really worked up over this paper now. All those imprudent, petty, little (and not so little) things my colleagues have done over the years have come flooding back to me today. And I am angry. I want to work through this anger constructively -- and creatively.In this paper, we address issues of accountability in the context of reflexively critiquing how feminist qualitative research is conventionally understood within the mainstream academy. The experiences of a feminist colleague, threatened with a legal suit by the male members of her department after informally presenting a chilly climate report, shape how we talk about these issues.(1) The concrete examples we give in this paper may be from different individuals' experiences, or from a composite of experiences; they may be fictional truths or perhaps even creative non-fiction.(2) Our data, if we can use the term, are not in a realist sense but rather are illustrative of a range of experiences. By using data in this way, our goal is analytical, to show how social processes work rather than to represent empirically a particular place or population of scholars. Some might call this approach polemical. For us, it is a way to poke at the boundaries of what we think and open up ways to communicate how power can be deployed in everyday settings within the academy that set parameters for (ac)counting (for) feminist qualitative research.As actors in a play, our characters in this paper take on experiences rather than have them. Thus, our story does not refer to or represent any one person, individual university, or single department. Indeed, one person might experience almost everything that is described here; another, only one; and still another might have a different set of experiences but reach the same set of conclusions. We hope, as our scenes (seens) unfold, there may perhaps be room for still more experiences, room for even more drama, room for more of (y)our own stories -- between the words, the exchanges, the lines. But, for now, for us, our tale dramatizes the workings of power/knowledge/space regimes, as embodied in the experiences of the characters who talk and walk through this text.Enough already, on with the story.* * *Feminist scholars' experiences in the academy often appear quite different from each other at first glance. Our first character below, for example, might have been hired within a context of recognizing methodological differences and divisions in her discipline. She might even have been hired to teach feminist theory and qualitative methods and told by those not sharing her perspective (either feminism or qualitative methods) that she was indeed welcome. …

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.984
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.034
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0160.031
Scholarly communication0.0150.012
Open science0.0020.007
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0060.001

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 head0.507
GPT teacher head0.615
Teacher spread0.108 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2000
Admission routes1
Has abstractyes

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