The application of feminist insights in communication and argumentation to the practice of argument
Bibliographic record
Abstract
In Chapter One, I discuss some of the characteristics and limitations associated with the traditionally oriented models of argumentation and communication that are the subject of critique in this thesis. In Chapter Two, I explore the idea that the socially and culturally defined attributes associated with one's gender identity carry over into our communicative and argumentative interchanges. In Chapter Three, I argue that because our perceptions and attitudes are effected by the limits of our social and cognitive environments, we should eliminate the predominance of adversarial connotations that surround the discourse of argument. In Chapter Four, I interpret and critique some alternative rhetorical communication theories to arrive at the conclusion that conceptualizing rhetorical argumentation solely in terms of having the goal of persuasion, is seriously limited. In Chapter Five, I give a brief synopsis of salient ideas from previous chapters. Additionally, I answer in the affirmative the research question of whether our argumentative and communicative practices should change in light of feminist insights. I also explore some limitations of feminist critiques of argumentation and communication. (Abstract shortened by UMI.)Dept. of Philosophy. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2000 .S545. Source: Masters Abstracts International, Volume: 40-03, page: 0574. Adviser: J. A. Blair. Thesis (M.A.)--University of Windsor (Canada), 2000.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.009 | 0.062 |
| Scholarly communication | 0.013 | 0.014 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".