Prez, Invisible woman Flashcards

1
Q

Explain how workplaces cannot be a meritocracy with the subordination of women?

A

Workplaces do performance based bonuses / reviews

BUT women are criticized in ways men aren’t (ex. she’s too bossy, abrasive, strict, etc)

White men are also rewarded more then women or ethnic minorities

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2
Q

What factor makes you less objective, and more likely to behave in a sexist way?

A

Thinking you are objective

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3
Q

Why did 40% of women leave tech companies after 10 years (compared to 17% of men)?

A

Workplace conditions, feeling stalled in one’s career, and being undermined by superiors

Women were also passed up for promotion (and had projects dismissed)

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4
Q

Explain how career progression in academia is depended on being a woman?

A

Often are reviewed with gender shown

When they are reviewed without showing names/gender, women’s papers are rated higher
- This is not standard practice tho

Women are cited less then men

Women also receive less credits

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5
Q

Explain how female academics/teachers are treated:

A

Students are more likely to ask grade boosts, extensions, and rule bending from female academics
- Toll on women mentally (who have to publish papers)

Women also do undervalued admin work (coffee, housekeeping) - (seen as rude if say no)

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6
Q

How are female teachers evaluated when they stray from teaching while male history?

A

Ppl say it’s useless info, or unrelated to main topics

Women are also rated harshly in student reviews (ex. ratemyprof)

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7
Q

What is “brilliance bias”?

A

We think of words like brilliant, intelligent, and smart

We will associate them with a man

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8
Q

Where does brilliance bias come from?

A

We have written so many female geniuses out of history

Men work in fields (STEM) that ppl ascribe to brilliance

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9
Q

In a study with male and female unattractive vs attractive pictures, who did ppl call geniuses more?

A

For men attractiveness didn’t matter

For women the more stereotypically feminine women were not considered feminine

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10
Q

What happens to children between ages of 5 and 6?

A

Girls start to be uninterested in a game presented as for (“really really smart kids”)
They were interested at 5, so what happened

They are being taught brilliance does not belong to them

Side note: When little boys are asked to draw a scientist 28% draw a woman (when they started school it was 50-50)

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11
Q

How are letters of recommendation gendered? (in hiring)

A

Women candidates often described with MORE communal terms (warm, kind) and LESS active terms (ambitious, self confident)

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12
Q

When is it harder to correct the brilliance bias?

A

Once it has already be learnt

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13
Q

Why don’t we see women and girls explicitly interested in computer science?

A
  • Misogyny in the field (that one asshole and his book)
  • Women may show interest differently
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14
Q

How is the algorithms in the hiring process implicitly gendered?

A

Male coders are often considered the norm (often geeks)

  • SO visiting a manga side was a predictor for being good at coding
  • But women do most unpaid reproductive labour (so not the time to visit manga sites)

SO the algorithm discriminated against women

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15
Q

What is the double gender data gap?

A
  • We don’t know what’s in the minds of coders who make the hiring algorithms

AND

  • We also don’t know how discriminatory they are (also how many of them are used)
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16
Q

How did google deal with the issue of women not nominating themselves for promotions? (women are socialized to be modest)

A

Held workshops to encourage women to be more like men (typical male default thinking)

17
Q

What did research find on self rating differences between men and women?

A

Men rated themselves as better then they are

Women rate more accurately

18
Q

When might women be put off from jobs?

A

When described on Ads with masculine traits (need aggressive, persistent people)

Then they say they aren’t interested cuz personal reasons

19
Q

How can a pay gap disappear?

A

When people disclose the pay data

One tech company had collected data on managers (and their salary choices) and had a committee monitor the pay data
- Pay gap pretty much eliminated