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Citizen Social Scientists’ Observations on Complex Tasks Match Trained Research Assistants’, Suggesting Lived Experiences are Valuable in Data Collection Cover

Citizen Social Scientists’ Observations on Complex Tasks Match Trained Research Assistants’, Suggesting Lived Experiences are Valuable in Data Collection

Open Access
|Dec 2021

Figures & Tables

cstp-6-1-449-g1.png
Figure 1

Recruitment brochure for citizen social science project “Eyes on OUR City.”

cstp-6-1-449-g2.png
Figure 2

Steps of qualitative analysis of observation booklets.

Table 1

Citizen scientist and research assistant demographic information (=162).

CITIZEN SCIENTISTS
(N = 162)
TRAINED SOCIAL SCIENCE RESEARCH ASSISTANTS
(N = 33)
AgeRange:19–72 years old22–45 years old
Mean:34.224.3
Gender
Female92 (58%)20 (61%)
Male67 (41%)7 (21%)
Other/non-binary3 (2%)1 (3%)
Decline to answer0 (0%)5 (15%)
Race/ethnicity
White49%39%
Black, African American4%0%
American Indian or Alaska Native2%0%
Asian/Asian American9%9%
Native Hawaiian or other Pacific Islander0%0%
Hispanic27%15%
≥ 2 categories8%24%
Decline to answer1%12%
Body Size
Do you consider yourself overweight? = Yes20%6%
Clinically overweight based on self-report of height and weight [BMI >25 < 29.9]30%18%
Clinically obese based on self-report* of height and weight
[BMI ≥ 30]
20%0%

[i] Notes: Self-reported height and weight found that 50% of the citizen scientists were either clinically overweight or obese based on BMI, although 80% of the volunteers indicated that they did not consider themselves overweight.

cstp-6-1-449-g3.png
Figure 3

Mean percentage of possible correct observations by exclusion domain for citizen scientists (n = 162) versus trained research assistants (n = 33). The whiskers represent standard deviation.

Table 2

Results of linear regression, predicting percent of possible exclusionary observations by category, based on citizen scientists’ initial vignette tests of their structural awareness and reported personal level of experiences of discrimination (note: one participant did not complete the structural awareness test).

DEPENDENTPREDICTORNUNSTANDARDIZED BETASTANDARD ERRORSTANDARDIZED BETATPFR2ADJUSTED R2
Observations of gender exclusions [% correct]Structural awareness pretest score [0–9]1610.9950.3470.2212.870.0058.2390.490.43
Observations of minority exclusions [% correct]Structural awareness pretest score [0–9]1611.2560.5040.1932.4910.0146.2060.0370.031
Observations of large body exclusions [% correct]Structural awareness pretest score [0–9]1610.0990.3490.0220.2840.7770.0800.000–0.006
Observations of elderly exclusions [% correct]Structural awareness pretest score [0–9]1610.0980.2480.0310.3970.6920.1580.001–0.005
Observations of gender exclusions [% correct]Discrimination experience score [0–22]162–0.0490.140–0.028bv bv16.3890.7270.1230.001–0.006
Observations of minority exclusions [% correct]Discrimination experience score [0–22]1620.1130.2020.0440.5600.5760.3140.002–0.004
Observations of large body exclusions [% correct]Discrimination experience score [0–22]162–0.0150.136–0.009–0.1070.9150.0120.000–0.006
Observations of elderly exclusions [% correct]Discrimination experience score [0–22]1620.0840.0980.0680.8580.3920.7360.005–0.002

[i] Note: Bolding added to column 1 for ease of distinguishing dependent variable; bolding of p values indicates significance.

DOI: https://doi.org/10.5334/cstp.449 | Journal eISSN: 2057-4991
Language: English
Submitted on: Jun 22, 2021
|
Accepted on: Nov 1, 2021
|
Published on: Dec 16, 2021
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2021 Cindi SturtzSreetharan, Alissa Ruth, Amber Wutich, Meskerem Glegziabher, Charlayne Mitchell, H. Russell Bernard, Alexandra Brewis, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.