N |
---|
150 |
gender | N | perc |
---|---|---|
man | 83 | 55.33 |
woman | 64 | 42.67 |
other | 3 | 2.00 |
race | N | perc |
---|---|---|
asian | 12 | 8.00 |
black | 9 | 6.00 |
hispanic | 5 | 3.33 |
multiracial | 8 | 5.33 |
white | 116 | 77.33 |
edu | N | perc |
---|---|---|
GED | 35 | 23.33 |
2yearColl | 16 | 10.67 |
4yearColl | 70 | 46.67 |
MA | 24 | 16.00 |
PHD | 5 | 3.33 |
employ_1 | N | perc |
---|---|---|
No | 1 | 0.67 |
Yes | 149 | 99.33 |
Are workers at your level and department in your workplace unionized?
membership_1 | N | perc |
---|---|---|
1 | 0.67 | |
No | 129 | 86.00 |
Yes | 20 | 13.33 |
IF NOT NO: Are you a union member?
membership_2 | N | perc |
---|---|---|
No | 4 | 19.05 |
Yes | 17 | 80.95 |
IF NOT YES: Would you be interested in joining a union?
membership_3 | N | perc |
---|---|---|
No | 62 | 41.33 |
Uncertain | 52 | 34.67 |
Yes | 36 | 24.00 |
Mean score of the following items:
1. My company’s success comes at the expense of me and my
colleagues
2. My personal goals are aligned with my company’s goals (R)
3. When my company gains, my colleagues and I gain as well (R)
4. My goals in life are inconsistent with my company’s goals
5. My company succeeds by sacrificing my and my colleagues’
wellbeing
6. My company’s focus on productivity comes at the expense of my
colleagues’ emotional safety
7. My company’s focus on productivity comes at the expense of my
colleagues’ physical safety
8. My company’s policies are good for the company but bad for me and my
colleagues
raw_alpha | std.alpha | G6(smc) | average_r | S/N | ase | mean | sd | median_r | |
---|---|---|---|---|---|---|---|---|---|
0.8808566 | 0.8818228 | 0.9019421 | 0.4825982 | 7.46187 | 0.0256325 | 2.9325 | 1.323408 | 0.4939133 |
hmm, pretty skewed. Let’s see which items are driving this.
ok, what if we took out item 7 and item 3?
raw_alpha | std.alpha | G6(smc) | average_r | S/N | ase | mean | sd | median_r | |
---|---|---|---|---|---|---|---|---|---|
0.8445608 | 0.8442503 | 0.8449607 | 0.4746317 | 5.420559 | 0.0341858 | 3.066667 | 1.398898 | 0.4844821 |
Mean score of the following items:
1. My manager’s success comes at the expense of me and my
colleagues
2. My personal goals are aligned with my manager’s goals (R)
3. When my manager gains, my colleagues and I gain as well (R)
4. My goals in life are inconsistent with my manager’s goals
5. My manager succeeds by sacrificing my and my colleagues’
wellbeing
6. My manager’s focus on productivity comes at the expense of my
colleagues’ emotional safety
7. My manager’s focus on productivity comes at the expense of my
colleagues’ physical safety
8. My manager’s policies are good for the company but bad for me and my
colleagues
raw_alpha | std.alpha | G6(smc) | average_r | S/N | ase | mean | sd | median_r | |
---|---|---|---|---|---|---|---|---|---|
0.9171793 | 0.9195324 | 0.9230122 | 0.5882096 | 11.42736 | 0.017467 | 2.6775 | 1.434383 | 0.5842608 |
I’ll take out the same two items for WPZS_M
raw_alpha | std.alpha | G6(smc) | average_r | S/N | ase | mean | sd | median_r | |
---|---|---|---|---|---|---|---|---|---|
0.8969156 | 0.8985172 | 0.8922851 | 0.5960654 | 8.853891 | 0.0226757 | 2.753333 | 1.539075 | 0.5755563 |
Prompt to participants:
Imagine that your company was trying to increase the company’s
profits (i.e., “the bottom line”).
There are several ways in which a company can increase its
profits.
In your experience, how do managers at your company try to increase
profits?
My company often tries to increase profits by
(decreasing/increasing/neither) for each of the following:
1. employee wages
2. safety measures
3. employee benefits
4. promotion opportunities
5. annual bonuses
6. overtime compensation
For each: decrease = -1; increase = 1, neither = 0. Then, I took the sum
of the six scores to create a tradeoffs score.
Mean score of the following items:
1. Unions are a positive force in this country
2. If I had to choose, I probably would not be a member of a labor union
(R)
3. I am glad that labor unions exist
4. People would be just as well off if there were no unions in this
country (R)
5. Unions are an embarrassment to our society (R)
6. I am proud of the labor movement in this country
7. Most people are better off without labor unions (R)
8. Employees are considerably better off when they belong to a labor
union
raw_alpha | std.alpha | G6(smc) | average_r | S/N | ase | mean | sd | median_r | |
---|---|---|---|---|---|---|---|---|---|
0.9338368 | 0.9359866 | 0.9414219 | 0.6463577 | 14.62173 | 0.0081862 | 5.0525 | 1.430087 | 0.6315802 |
Mean score of the following items:
1. A union will improve how fairly decisions are made at my
company
2. A union will lead to more respect for workers from my company
union_inst_1 | union_inst_2 | |
---|---|---|
union_inst_1 | 1.0000000 | 0.8887424 |
union_inst_2 | 0.8887424 | 1.0000000 |
Single item: If an election were held tomorrow to decide whether your workplace would have a union or not, what would be your vote?
union_vote | N |
---|---|
No (against unionization) | 52 |
Yes (for unionization) | 98 |
Mean score of the following items:
1. I have ample opportunity to express my views on decisions that affect
me at my workplace
2. My company’s rules require that decisions be neutral and
unbiased
3. My company’s procedures and policies are fair
4. My company’s rules are applied consistently across the
organization
5. My company makes every effort to be fair when making decisions
6. My company’s rules protect my rights
7. My company’s rules ensure that workers are treated fairly
8. My company makes decisions fairly
raw_alpha | std.alpha | G6(smc) | average_r | S/N | ase | mean | sd | median_r | |
---|---|---|---|---|---|---|---|---|---|
0.977682 | 0.9778675 | 0.9765667 | 0.8466919 | 44.18249 | 0.0027585 | 5.144167 | 1.641261 | 0.8516256 |
Mean score of the following items:
1. The compensation and benefits that my company’s employees receive are
fair
2. The compensation and benefits I receive reflect my contributions to
my company
3. I feel fairly compensated as an employee
raw_alpha | std.alpha | G6(smc) | average_r | S/N | ase | mean | sd | median_r | |
---|---|---|---|---|---|---|---|---|---|
0.9648347 | 0.9649056 | 0.9491584 | 0.9016218 | 27.49457 | 0.004984 | 4.884444 | 1.744272 | 0.9021872 |
Mean score of the following items:
1. The free enterprise system mainly benefits the rich and
powerful
2. The working classes should have more say in running society
3. Workers get their fair share of the economic rewards of society
(R)
4. The work of the laboring classes is exploited by the rich for their
own benefit
5. Wealthy people carry their fair share of the burdens in this country
(R)
6. Workers should be represented on the board of directors of
companies
7. The most important work in America is done by the laboring
classes
raw_alpha | std.alpha | G6(smc) | average_r | S/N | ase | mean | sd | median_r | |
---|---|---|---|---|---|---|---|---|---|
0.8746212 | 0.8788612 | 0.8859508 | 0.508944 | 7.254992 | 0.0157122 | 5.208571 | 1.277928 | 0.5071473 |
Ok, now that we’re a bit more familiar with the variables, let’s take a look at some relationships between them. I’ll start with a correlation matrix:
Ok, some decent correlations. Stronger with company than with manager. What about voting intention (no = 0; yes = 1). Let’s just compare scores on some of these measures for those who would vote vs. those who would not vote.
measure | No (against unionization) | Yes (for unionization) |
---|---|---|
WPZS_C | 2.3281250 | 3.2169118 |
WPZS_C_short | 2.4270833 | 3.3676471 |
WPZS_M | 2.0714286 | 2.9131944 |
WPZS_M_short | 2.1071429 | 3.0046296 |
tradeoffs | 0.1818182 | -0.8214286 |
union_att | 3.7788462 | 5.7283163 |
union_inst | 2.9903846 | 5.8112245 |
just_proc | 5.5697115 | 4.9183673 |
just_dist | 5.6089744 | 4.5000000 |
identity | 4.7467949 | 4.6513605 |
marx | 4.4093407 | 5.6326531 |
pretty cool. I think these are all pretty much the relationships we’d expect. The identity question is pretty interesting.
Alright, let’s run some stats. Before we do, I’ll just note that the sample size is pretty small, so we’re really looking for p-values here. We’re looking for direction of effect and effect sizes.
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 0.35 | [0.04, 0.66] | 2.27 | 48 | .028 |
WPZS C short | 0.11 | [0.01, 0.20] | 2.31 | 48 | .025 |
Note. Union Vote DV: No = 0; Yes = 1
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 0.98 | [-0.36, 2.33] | 1.47 | 46 | .148 |
WPZS C short | -0.06 | [-0.35, 0.23] | -0.44 | 46 | .665 |
Identity | -0.13 | [-0.35, 0.10] | -1.12 | 46 | .266 |
WPZS C short \(\times\) Identity | 0.04 | [-0.01, 0.09] | 1.45 | 46 | .153 |
Note. Union Vote DV: No = 0; Yes = 1
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | -0.28 | [-1.37, 0.82] | -0.51 | 45 | .614 |
WPZS C short | 0.06 | [-0.06, 0.17] | 0.97 | 45 | .337 |
Marx | 0.16 | [0.06, 0.26] | 3.18 | 45 | .003 |
Just proc | -0.01 | [-0.11, 0.10] | -0.15 | 45 | .880 |
Just dist | 0.00 | [-0.09, 0.09] | 0.00 | 45 | .997 |
Note. Union Vote DV: No = 0; Yes = 1
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 0.51 | [0.25, 0.76] | 3.92 | 48 | < .001 |
WPZS M short | 0.08 | [0.00, 0.16] | 1.90 | 48 | .063 |
Note. Union Vote DV: No = 0; Yes = 1
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 0.09 | [-0.80, 0.98] | 0.20 | 46 | .846 |
WPZS M short | 0.11 | [-0.09, 0.31] | 1.10 | 46 | .277 |
Identity | 0.06 | [-0.10, 0.22] | 0.74 | 46 | .460 |
WPZS M short \(\times\) Identity | 0.00 | [-0.04, 0.05] | 0.16 | 46 | .873 |
Note. Union Vote DV: No = 0; Yes = 1
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 0.08 | [-0.80, 0.97] | 0.19 | 45 | .850 |
WPZS M short | 0.07 | [-0.04, 0.18] | 1.36 | 45 | .181 |
Marx | 0.08 | [-0.03, 0.19] | 1.52 | 45 | .135 |
Just proc | 0.11 | [0.00, 0.21] | 2.04 | 45 | .048 |
Just dist | -0.11 | [-0.20, -0.02] | -2.35 | 45 | .023 |
Note. Union Vote DV: No = 0; Yes = 1
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 0.55 | [0.40, 0.69] | 7.68 | 48 | < .001 |
Tradeoffs | -0.04 | [-0.09, 0.02] | -1.35 | 48 | .184 |
Note. Union Vote DV: No = 0; Yes = 1
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 0.40 | [-0.01, 0.82] | 1.97 | 46 | .055 |
Tradeoffs | 0.01 | [-0.14, 0.17] | 0.19 | 46 | .850 |
Identity | 0.03 | [-0.05, 0.12] | 0.81 | 46 | .424 |
Tradeoffs \(\times\) Identity | -0.01 | [-0.05, 0.02] | -0.80 | 46 | .430 |
Note. Union Vote DV: No = 0; Yes = 1
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | -0.52 | [-1.43, 0.40] | -1.14 | 45 | .261 |
Tradeoffs | -0.02 | [-0.08, 0.03] | -0.81 | 45 | .419 |
Marx | 0.19 | [0.08, 0.30] | 3.53 | 45 | .001 |
Just proc | 0.02 | [-0.13, 0.16] | 0.24 | 45 | .811 |
Just dist | 0.00 | [-0.14, 0.13] | -0.05 | 45 | .963 |
Note. Union Vote DV: No = 0; Yes = 1
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 4.39 | [3.45, 5.33] | 9.38 | 48 | < .001 |
WPZS C short | 0.22 | [-0.06, 0.50] | 1.56 | 48 | .126 |
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 6.70 | [2.61, 10.78] | 3.30 | 46 | .002 |
WPZS C short | -0.20 | [-1.08, 0.68] | -0.46 | 46 | .648 |
Identity | -0.37 | [-1.05, 0.31] | -1.10 | 46 | .279 |
WPZS C short \(\times\) Identity | 0.06 | [-0.10, 0.22] | 0.73 | 46 | .468 |
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 2.50 | [-0.19, 5.18] | 1.87 | 45 | .068 |
WPZS C short | -0.05 | [-0.34, 0.23] | -0.38 | 45 | .702 |
Marx | 0.65 | [0.40, 0.90] | 5.28 | 45 | < .001 |
Just proc | -0.02 | [-0.28, 0.24] | -0.13 | 45 | .895 |
Just dist | -0.12 | [-0.34, 0.10] | -1.08 | 45 | .286 |
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 4.57 | [3.70, 5.44] | 10.57 | 48 | < .001 |
WPZS M short | 0.16 | [-0.12, 0.44] | 1.17 | 48 | .248 |
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 1.50 | [-1.41, 4.41] | 1.04 | 46 | .304 |
WPZS M short | 0.69 | [0.03, 1.35] | 2.09 | 46 | .042 |
Identity | 0.55 | [0.02, 1.08] | 2.07 | 46 | .044 |
WPZS M short \(\times\) Identity | -0.09 | [-0.23, 0.06] | -1.19 | 46 | .240 |
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 0.95 | [-1.68, 3.58] | 0.73 | 45 | .470 |
WPZS M short | 0.15 | [-0.17, 0.47] | 0.93 | 45 | .356 |
Marx | 0.61 | [0.29, 0.92] | 3.84 | 45 | < .001 |
Just proc | 0.34 | [0.03, 0.66] | 2.19 | 45 | .034 |
Just dist | -0.25 | [-0.53, 0.02] | -1.85 | 45 | .070 |
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 5.05 | [4.64, 5.46] | 24.63 | 48 | < .001 |
Tradeoffs | -0.11 | [-0.26, 0.05] | -1.38 | 48 | .173 |
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 5.22 | [4.01, 6.42] | 8.71 | 46 | < .001 |
Tradeoffs | -0.17 | [-0.61, 0.28] | -0.76 | 46 | .450 |
Identity | -0.04 | [-0.29, 0.21] | -0.33 | 46 | .746 |
Tradeoffs \(\times\) Identity | 0.02 | [-0.08, 0.12] | 0.33 | 46 | .746 |
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 0.31 | [-1.80, 2.43] | 0.30 | 45 | .767 |
Tradeoffs | -0.05 | [-0.18, 0.07] | -0.89 | 45 | .380 |
Marx | 0.81 | [0.56, 1.06] | 6.50 | 45 | < .001 |
Just proc | 0.08 | [-0.25, 0.41] | 0.49 | 45 | .627 |
Just dist | 0.02 | [-0.30, 0.34] | 0.11 | 45 | .913 |
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 5.93 | [4.96, 6.90] | 12.31 | 48 | < .001 |
Just proc | -0.56 | [-0.74, -0.38] | -6.25 | 48 | < .001 |
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 4.89 | [3.90, 5.87] | 10.00 | 48 | < .001 |
Just dist | -0.39 | [-0.59, -0.19] | -3.99 | 48 | < .001 |
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 4.54 | [2.66, 6.43] | 4.85 | 46 | < .001 |
Just dist | 0.32 | [-0.18, 0.82] | 1.30 | 46 | .200 |
Just proc | -0.15 | [-0.56, 0.27] | -0.72 | 46 | .475 |
Just dist \(\times\) Just proc | -0.09 | [-0.18, 0.00] | -1.93 | 46 | .059 |
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 5.87 | [4.81, 6.92] | 11.17 | 48 | < .001 |
Just proc | -0.61 | [-0.81, -0.41] | -6.24 | 48 | < .001 |
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 5.27 | [4.17, 6.37] | 9.65 | 48 | < .001 |
Just dist | -0.51 | [-0.72, -0.30] | -4.88 | 48 | < .001 |
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 7.74 | [5.49, 9.99] | 6.92 | 46 | < .001 |
Just dist | -0.59 | [-1.13, -0.06] | -2.22 | 46 | .031 |
Just proc | -0.85 | [-1.41, -0.30] | -3.08 | 46 | .003 |
Just dist \(\times\) Just proc | 0.08 | [-0.02, 0.19] | 1.56 | 46 | .125 |
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | -3.52 | [-5.95, -1.08] | -2.90 | 48 | .006 |
Just proc | 0.60 | [0.15, 1.05] | 2.70 | 48 | .009 |
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | -3.49 | [-5.66, -1.32] | -3.23 | 48 | .002 |
Just dist | 0.61 | [0.21, 1.02] | 3.04 | 48 | .004 |
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | -0.55 | [-5.23, 4.13] | -0.24 | 46 | .813 |
Just dist | -0.36 | [-1.65, 0.93] | -0.56 | 46 | .576 |
Just proc | -0.65 | [-1.95, 0.64] | -1.01 | 46 | .316 |
Just dist \(\times\) Just proc | 0.19 | [-0.05, 0.43] | 1.59 | 46 | .120 |
Alright, let’s explore political ideology as a predictor. First, some correlations:
term | ideo_gen | ideo_soc | ideo_econ |
---|---|---|---|
ideo_gen | NA | 0.8974813 | 0.8724160 |
ideo_soc | 0.8974813 | NA | 0.7096104 |
ideo_econ | 0.8724160 | 0.7096104 | NA |
WPZS_C_short | -0.1085979 | -0.0480711 | -0.1007826 |
WPZS_M_short | -0.0123028 | 0.0108648 | -0.0798525 |
tradeoffs | 0.2197275 | 0.0309315 | 0.2834323 |
union_att | -0.5874541 | -0.5647248 | -0.6003114 |
union_inst | -0.4149780 | -0.3794706 | -0.4443054 |
just_proc | 0.1231759 | 0.0954983 | 0.1654965 |
just_dist | 0.2624205 | 0.1913319 | 0.3076366 |
identity | 0.1171984 | 0.0814081 | 0.1183239 |
marx | -0.5288009 | -0.4807464 | -0.5397160 |
hmm, pretty weak correlations with our zero-sum measures. That’s pretty good if we want to show that its not just about ideology. Maybe unsurprisingly, union attitudes, union instrumentality, and marxist beliefs are strongly correlated with ideology. Ok, let’s run some analyses.
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 0.78 | [0.11, 1.46] | 2.33 | 46 | .024 |
WPZS C short | 0.07 | [-0.12, 0.27] | 0.73 | 46 | .468 |
Ideo gen | -0.11 | [-0.28, 0.06] | -1.32 | 46 | .194 |
WPZS C short \(\times\) Ideo gen | 0.01 | [-0.04, 0.06] | 0.26 | 46 | .792 |
Note. Union Vote DV: No = 0; Yes = 1
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 0.86 | [0.37, 1.36] | 3.52 | 46 | .001 |
WPZS M short | 0.08 | [-0.08, 0.24] | 1.01 | 46 | .316 |
Ideo gen | -0.10 | [-0.23, 0.03] | -1.53 | 46 | .132 |
WPZS M short \(\times\) Ideo gen | 0.00 | [-0.04, 0.04] | -0.05 | 46 | .957 |
Note. Union Vote DV: No = 0; Yes = 1
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 0.93 | [0.61, 1.25] | 5.86 | 46 | < .001 |
Tradeoffs | -0.04 | [-0.17, 0.10] | -0.57 | 46 | .569 |
Ideo gen | -0.10 | [-0.18, -0.03] | -2.75 | 46 | .008 |
Tradeoffs \(\times\) Ideo gen | 0.00 | [-0.02, 0.03] | 0.29 | 46 | .772 |
Note. Union Vote DV: No = 0; Yes = 1
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 6.37 | [4.60, 8.13] | 7.26 | 46 | < .001 |
WPZS C short | 0.09 | [-0.43, 0.60] | 0.34 | 46 | .734 |
Ideo gen | -0.51 | [-0.95, -0.07] | -2.31 | 46 | .025 |
WPZS C short \(\times\) Ideo gen | 0.02 | [-0.11, 0.15] | 0.30 | 46 | .767 |
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 5.60 | [4.16, 7.05] | 7.80 | 46 | < .001 |
WPZS M short | 0.40 | [-0.07, 0.86] | 1.73 | 46 | .091 |
Ideo gen | -0.27 | [-0.65, 0.11] | -1.41 | 46 | .166 |
WPZS M short \(\times\) Ideo gen | -0.08 | [-0.20, 0.05] | -1.21 | 46 | .234 |
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 6.63 | [5.81, 7.46] | 16.23 | 46 | < .001 |
Tradeoffs | -0.15 | [-0.50, 0.19] | -0.89 | 46 | .377 |
Ideo gen | -0.43 | [-0.62, -0.23] | -4.46 | 46 | < .001 |
Tradeoffs \(\times\) Ideo gen | 0.03 | [-0.05, 0.10] | 0.71 | 46 | .478 |
hmm, political ideology is just too strong a predictor of general union attitudes to see anything. It does look, though, like the effect on WPZS manager and tradeoffs is most pronounced for liberals than for conservatives. Not to over-interpret this, but maybe it’s because liberals more readily translate zero-sum beliefs at work to labor unions.
let’s do all of this for SES as well.
term | SES |
---|---|
SES | NA |
WPZS_C_short | -0.0098908 |
WPZS_M_short | -0.2896249 |
tradeoffs | -0.0127799 |
union_att | -0.1692036 |
union_inst | -0.0451731 |
just_proc | 0.1848856 |
just_dist | 0.2151716 |
identity | 0.2388429 |
marx | -0.1830966 |
Not a lot here. I’m guessing it’s mostly because we don’t have a lot of variance in SES. Nonetheless, let’s explore SES in some analyses:
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 0.86 | [-0.25, 1.98] | 1.55 | 45 | .127 |
WPZS C short | -0.08 | [-0.43, 0.27] | -0.45 | 45 | .653 |
SES | -0.10 | [-0.32, 0.12] | -0.95 | 45 | .346 |
WPZS C short \(\times\) SES | 0.04 | [-0.03, 0.11] | 1.10 | 45 | .279 |
Note. Union Vote DV: No = 0; Yes = 1
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 0.81 | [-0.24, 1.85] | 1.55 | 46 | .129 |
WPZS M short | 0.02 | [-0.27, 0.30] | 0.11 | 46 | .914 |
SES | -0.05 | [-0.23, 0.13] | -0.59 | 46 | .560 |
WPZS M short \(\times\) SES | 0.01 | [-0.04, 0.06] | 0.42 | 46 | .678 |
Note. Union Vote DV: No = 0; Yes = 1
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 0.73 | [0.23, 1.23] | 2.94 | 45 | .005 |
Tradeoffs | -0.17 | [-0.34, 0.01] | -1.90 | 45 | .064 |
SES | -0.04 | [-0.14, 0.06] | -0.80 | 45 | .430 |
Tradeoffs \(\times\) SES | 0.03 | [-0.01, 0.06] | 1.60 | 45 | .116 |
Note. Union Vote DV: No = 0; Yes = 1
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 3.31 | [0.01, 6.61] | 2.02 | 45 | .050 |
WPZS C short | 0.73 | [-0.30, 1.76] | 1.42 | 45 | .162 |
SES | 0.23 | [-0.42, 0.88] | 0.71 | 45 | .479 |
WPZS C short \(\times\) SES | -0.11 | [-0.31, 0.09] | -1.09 | 45 | .283 |
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 4.49 | [0.98, 8.00] | 2.57 | 46 | .013 |
WPZS M short | 0.31 | [-0.65, 1.27] | 0.65 | 46 | .517 |
SES | 0.02 | [-0.58, 0.63] | 0.08 | 46 | .936 |
WPZS M short \(\times\) SES | -0.03 | [-0.21, 0.14] | -0.38 | 46 | .704 |
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 6.43 | [5.00, 7.87] | 9.02 | 45 | < .001 |
Tradeoffs | -0.19 | [-0.70, 0.32] | -0.75 | 45 | .457 |
SES | -0.29 | [-0.59, 0.00] | -2.02 | 45 | .049 |
Tradeoffs \(\times\) SES | 0.02 | [-0.08, 0.11] | 0.33 | 45 | .746 |
Not a lot here. hmm.
There are 17 people who are in a union and 36 more who would join a union if their workplace had one. Let’s compare them to the other participants.
members | WPZS_C_short | WPZS_M_short | tradeoffs | N |
---|---|---|---|---|
Current Members | 3.571429 | 2.366667 | 0.4000000 | 17 |
Others | 2.812500 | 2.229167 | -0.4242424 | 97 |
Want-to-be Members | 3.484849 | 4.192308 | -0.5833333 | 36 |
oh, yeah, we’re seeing some differences here. Union members have highest zero-sum beliefs and would-be members are a close second. Not enough power here for stats, but this has some potential. We do similar trends for the voting intention question.
There’s a lot here. To refresh out memory, this is the distribution:
Let’s see some analyses:
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 0.69 | [0.47, 0.90] | 6.20 | 148 | < .001 |
Identity | -0.01 | [-0.05, 0.04] | -0.31 | 148 | .756 |
No effect on voting intentions. How about as a moderator?
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 0.98 | [-0.36, 2.33] | 1.47 | 46 | .148 |
Identity | -0.13 | [-0.35, 0.10] | -1.12 | 46 | .266 |
WPZS C short | -0.06 | [-0.35, 0.23] | -0.44 | 46 | .665 |
Identity \(\times\) WPZS C short | 0.04 | [-0.01, 0.09] | 1.45 | 46 | .153 |
pretty cool! Stronger effects for those who identify with their workplace. Let’s see some more:
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 0.09 | [-0.80, 0.98] | 0.20 | 46 | .846 |
Identity | 0.06 | [-0.10, 0.22] | 0.74 | 46 | .460 |
WPZS M short | 0.11 | [-0.09, 0.31] | 1.10 | 46 | .277 |
Identity \(\times\) WPZS M short | 0.00 | [-0.04, 0.05] | 0.16 | 46 | .873 |
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | 0.40 | [-0.01, 0.82] | 1.97 | 46 | .055 |
Identity | 0.03 | [-0.05, 0.12] | 0.81 | 46 | .424 |
Tradeoffs | 0.01 | [-0.14, 0.17] | 0.19 | 46 | .850 |
Identity \(\times\) Tradeoffs | -0.01 | [-0.05, 0.02] | -0.80 | 46 | .430 |
a = -0.58 (p = 0)
b = -0.45 (p = 0)
c = 0.8 (p = 0)
c’ = 0.54 (p = 0)
a = -0.64 (p = 0)
b = -0.15 (p = 0.095)
c = 0.8 (p = 0)
c’ = 0.71 (p = 0)
a = 0.57 (p = 0)
b = 0.01 (p = 0.844)
c = 0.8 (p = 0)
c’ = 0.8 (p = 0)
a = -0.41 (p = 0)
b = -0.7 (p = 0)
c = 0.58 (p = 0)
c’ = 0.29 (p = 0)
a = -0.51 (p = 0)
b = -0.43 (p = 0)
c = 0.58 (p = 0)
c’ = 0.36 (p = 0)
a = 0.6 (p = 0)
b = 0.04 (p = 0.446)
c = 0.58 (p = 0)
c’ = 0.56 (p = 0)
Workplace Zero-Sum Company is doing a lot of explanatory work here.
Grain of salt and all, but still, pretty cool.
Alright, let’s explore marxist work beliefs a little bit. Distribution for refresher:
ok, first I’ll just say that we got a bunch of marxists in our sample. Different project and all, but I’d guess that this would be pretty consistent across the population (for lower incomes / working class). Just for fun - let’s see the distribution broken down by “ideology.”
Yeah, even the “slightly conservative” and “conservative” labels are above the mid-point in MARXIST work beliefs. Love the class solidarity (doesn’t transalte to the ballot, ofc, but that’s part of the challenge). Anyway, sorry, I digress.
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | -0.59 | [-1.53, 0.34] | -1.27 | 46 | .210 |
WPZS C short | 0.15 | [-0.16, 0.46] | 0.99 | 46 | .327 |
Marx | 0.21 | [0.02, 0.40] | 2.28 | 46 | .027 |
WPZS C short \(\times\) Marx | -0.02 | [-0.08, 0.04] | -0.62 | 46 | .541 |
Note. Union Vote DV: No = 0; Yes = 1
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | -0.62 | [-1.82, 0.58] | -1.04 | 46 | .306 |
WPZS M short | 0.27 | [-0.14, 0.68] | 1.33 | 46 | .189 |
Marx | 0.22 | [0.00, 0.44] | 2.02 | 46 | .049 |
WPZS M short \(\times\) Marx | -0.04 | [-0.11, 0.03] | -1.06 | 46 | .293 |
Note. Union Vote DV: No = 0; Yes = 1
Predictor | \(b\) | 95% CI | \(t\) | \(\mathit{df}\) | \(p\) |
---|---|---|---|---|---|
Intercept | -0.46 | [-0.98, 0.07] | -1.76 | 46 | .085 |
Tradeoffs | 0.13 | [-0.16, 0.42] | 0.91 | 46 | .367 |
Marx | 0.19 | [0.09, 0.29] | 3.95 | 46 | < .001 |
Tradeoffs \(\times\) Marx | -0.03 | [-0.08, 0.02] | -1.06 | 46 | .295 |
Note. Union Vote DV: No = 0; Yes = 1
Social identity
Mean score of the following items:
1. I feel strong ties with my company
2. I identify with my company’s community
3. I see myself as a member of my company’s community
4. When someone praises my company, it feels like a personal compliment to me
5. I am proud to be a member of my company’s community
6. Being an employee at my company says a lot about who i am as a person
Internal consistency
Distribution