Metadata

Description

Dataset name: The Power of Conformity in Citizens’ Blame

Data set for Sievert, M., Vogel, D., Reinders, T., & Ahmed, W.. (2019). The Power of Conformity in Citizens’ Blame: Evidence from a Survey Experiment. Public Performance & Management Review.

Metadata for search engines

Temporal Coverage: April 2017
Spatial Coverage: Hamburg, Germany
Citation: Sievert, M., Vogel, D., Reinders, T., & Ahmed, W. (2019). The Power of Conformity in Citizens’ Blame: Evidence from a Survey Experiment. Public Performance & Management Review.
URL:
Identifier: https://doi.org/10.7910/DVN/KYOABG
Date published: 2019-06-21
Creator:Martin Sievert, Dominik Vogel, Tim Reinders, Waqar Ahmed
- keywords: quality_time_management, quality_service_on_time, quality_amount_of_staff, quality_overall, attention_check, blame_responsible, blame_fault, blame_time_management, blame_substantial_service, blame_employees, blame_overall, blame_willing, political_orientation, visit_service_center, yearbirth, gender and group

Variables

quality_time_management

time management regarding the appointments for citizens?

Distribution

0 missing values.

Summary statistics

name	label	data_type	value_labels	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
quality_time_management	time management regarding the appointments for citizens?	numeric	0. Extremely poor, 100. Extremely good	0	362	362	32.62	21.12	0	16	30	46	97	▆▇▇▅▅▂▁▁

Value labels

Extremely poor: 0
Extremely good: 100

quality_service_on_time

certainty that citizens receive substantial service on time?

Distribution

0 missing values.

Summary statistics

name	label	data_type	value_labels	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
quality_service_on_time	certainty that citizens receive substantial service on time?	numeric	0. Extremely poor, 100. Extremely good	0	362	362	35.5	22.53	0	19	31.5	50	100	▅▇▆▅▃▂▁▁

Value labels

Extremely poor: 0
Extremely good: 100

quality_amount_of_staff

amount of staff that is working in the registration offices?

Distribution

0 missing values.

Summary statistics

name	label	data_type	value_labels	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
quality_amount_of_staff	amount of staff that is working in the registration offices?	numeric	0. Extremely poor, 100. Extremely good	0	362	362	34.81	23.07	0	17.25	30	50	100	▅▇▆▅▃▃▁▁

Value labels

Extremely poor: 0
Extremely good: 100

quality_overall

Overall, what do you think of the quality of the waiting time for appointments in registration offices as presented before?

Distribution

0 missing values.

Summary statistics

name	label	data_type	value_labels	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
quality_overall	Overall, what do you think of the quality of the waiting time for appointments in registration offices as presented before?	numeric	0. Extremely poor, 100. Extremely good	0	362	362	28.68	20.26	0	14.25	24	40	100	▆▇▅▃▂▁▁▁

Value labels

Extremely poor: 0
Extremely good: 100

attention_check

In which timeframe will you get an appointment in the registration offices in Hamburg?

Distribution

8 missing values.

Summary statistics

name	label	data_type	value_labels	missing	complete	n	empty	n_unique	min	max
attention_check	In which timeframe will you get an appointment in the registration offices in Hamburg?	character	1 - 2 weeks. 1–2 weeks, 3 - 5 weeks. 3–5 weeks, 6 - 8 weeks. 6–8 weeks	8	354	362	0	3	11	11

Value labels

1–2 weeks: 1 - 2 weeks
3–5 weeks: 3 - 5 weeks
6–8 weeks: 6 - 8 weeks

blame_responsible

How much do you think local politicians are responsible for the given situation in the registration offices?

Distribution

26 missing values.

Summary statistics

name	label	data_type	value_labels	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
blame_responsible	How much do you think local politicians are responsible for the given situation in the registration offices?	numeric	0. Not at all responsible, 100. Completely responsible	26	336	362	55.38	25.17	1	36.75	56	75	100	▂▅▅▇▇▆▆▅

Value labels

Not at all responsible: 0
Completely responsible: 100

blame_fault

How much do you think the given situation is local politician’s fault?

Distribution

26 missing values.

Summary statistics

name	label	data_type	value_labels	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
blame_fault	How much do you think the given situation is local politician’s fault?	numeric	0. Not at all politicians’ fault, 100. Completely politicians’ fault	26	336	362	52.84	25.24	1	33.75	51	72.25	100	▂▅▅▇▆▆▅▅

Value labels

Not at all politicians’ fault: 0
Completely politicians’ fault: 100

blame_time_management

Time management regarding the appointments for citizens?

Distribution

27 missing values.

Summary statistics

name	label	data_type	value_labels	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
blame_time_management	Time management regarding the appointments for citizens?	numeric	0. Deserving no blame at all, 100. Completely deserving blame	27	335	362	46.88	24.85	0	28	45	65	100	▃▆▇▇▆▅▃▃

Value labels

Deserving no blame at all: 0
Completely deserving blame: 100

blame_substantial_service

Certainty that citizens receive substantial service on time?

Distribution

26 missing values.

Summary statistics

name	label	data_type	value_labels	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
blame_substantial_service	Certainty that citizens receive substantial service on time?	numeric	0. Deserving no blame at all, 100. Completely deserving blame	26	336	362	46.82	23.57	0	28.75	48	62.25	100	▂▆▆▇▇▅▂▂

Value labels

Deserving no blame at all: 0
Completely deserving blame: 100

blame_employees

Amount of employees that are working in the registration offices?

Distribution

27 missing values.

Summary statistics

name	label	data_type	value_labels	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
blame_employees	Amount of employees that are working in the registration offices?	numeric	0. Deserving no blame at all, 100. Completely deserving blame	27	335	362	55.79	26.25	0	34	58	76	100	▂▃▆▆▇▇▅▆

Value labels

Deserving no blame at all: 0
Completely deserving blame: 100

blame_overall

Overall, to what extent do you believe local politicians are deserving blame for the waiting times as displayed to you earlier?

Distribution

26 missing values.

Summary statistics

name	label	data_type	value_labels	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
blame_overall	Overall, to what extent do you believe local politicians are deserving blame for the waiting times as displayed to you earlier?	numeric	0. Deserving no blame at all, 100. Completely deserving blame	26	336	362	49.48	23.81	0	30	50	67	100	▂▆▅▇▇▆▃▂

Value labels

Deserving no blame at all: 0
Completely deserving blame: 100

blame_willing

Overall, to what extent are you willing to attribute blame to local politicians for the waiting times as displayed earlier?

Distribution

32 missing values.

Summary statistics

name	label	data_type	value_labels	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
blame_willing	Overall, to what extent are you willing to attribute blame to local politicians for the waiting times as displayed earlier?	numeric	0. Not at all willing, 100. Completely willing	32	330	362	46.65	24.51	0	28.25	45	66	100	▃▅▇▇▅▆▂▂

Value labels

Not at all willing: 0
Completely willing: 100

political_orientation

In politics people sometimes talk of ‘left’ and ‘right’. Where would you place yourself on a scale from 0 to 10?

Distribution

34 missing values.

Summary statistics

name	label	data_type	value_labels	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
political_orientation	In politics people sometimes talk of ‘left’ and ‘right’. Where would you place yourself on a scale from 0 to 10?	numeric	0. extreme left, 10. extreme right	34	328	362	3.87	1.61	0	3	4	5	9	▁▅▇▅▆▂▁▁

Value labels

extreme left: 0
extreme right: 10

visit_service_center

Did you attend a registration office in the last 12 months?

Distribution

0 missing values.

Summary statistics

name	label	data_type	value_labels	missing	complete	n	empty	n_unique	min	max
visit_service_center	Did you attend a registration office in the last 12 months?	character	No. No, Yes. Yes, NA. N/A	0	362	362	0	3	2	3

Value labels

No: No
Yes: Yes
N/A: NA

yearbirth

What year were you born?

Distribution

34 missing values.

Summary statistics

name	label	data_type	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
yearbirth	What year were you born?	numeric	34	328	362	1990.71	4.32	1971	1989	1991	1993.25	1998	▁▁▁▁▂▇▅▃

gender

How do you describe your gender identity?

Distribution

34 missing values.

Summary statistics

name	label	data_type	value_labels	missing	complete	n	empty	n_unique	min	max
gender	How do you describe your gender identity?	character	Male. Male, Female. Female	34	328	362	0	3	4	6

Value labels

Male: Male
Female: Female

group

Treatment group

Distribution

0 missing values.

Summary statistics

name	label	data_type	value_labels	missing	complete	n	mean	sd	p0	p25	p50	p75	p100	hist
group	Treatment group	numeric	0. Control, 1. Public opinion in favor of blaming, 2. Public opinion not in favor of blaming, 3. High intensity of pre-existing blame, 4. No pre-existing blame	0	362	362	2.05	1.44	0	1	2	3	4	▇▆▁▇▁▇▁▇

Value labels

Control: 0
Public opinion in favor of blaming: 1
Public opinion not in favor of blaming: 2
High intensity of pre-existing blame: 3
No pre-existing blame: 4

Codebook table

JSON-LD metadata

The following JSON-LD can be found by search engines, if you share this codebook publicly on the web.

{
  "name": "The Power of Conformity in Citizens' Blame",
  "description": "Data set for Sievert, M., Vogel, D., Reinders, T., & Ahmed, W.. (2019). The Power of Conformity in Citizens' Blame: Evidence from a Survey Experiment. Public Performance & Management Review.\n\n\n## Table of variables\nThis table contains variable names, labels, their central tendencies and other attributes.\n\n|name                      |label                                                                                                                           |data_type |value_labels                                                                                                                                                    |missing |complete |n   |empty |n_unique |min |max |mean    |sd    |p0   |p25   |p50  |p75     |p100 |hist     |\n|:-------------------------|:-------------------------------------------------------------------------------------------------------------------------------|:---------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------|:-------|:--------|:---|:-----|:--------|:---|:---|:-------|:-----|:----|:-----|:----|:-------|:----|:--------|\n|quality_time_management   |time management regarding the appointments for citizens?                                                                        |numeric   |0. Extremely poor, - 100. Extremely good                                                                                                                          |0       |362      |362 |NA    |NA       |NA  |NA  |32.62   |21.12 |0    |16    |30   |46      |97   |▆▇▇▅▅▂▁▁ |\n|quality_service_on_time   |certainty that citizens receive substantial service on time?                                                                    |numeric   |0. Extremely poor, - 100. Extremely good                                                                                                                          |0       |362      |362 |NA    |NA       |NA  |NA  |35.5    |22.53 |0    |19    |31.5 |50      |100  |▅▇▆▅▃▂▁▁ |\n|quality_amount_of_staff   |amount of staff that is working in the registration offices?                                                                    |numeric   |0. Extremely poor, - 100. Extremely good                                                                                                                          |0       |362      |362 |NA    |NA       |NA  |NA  |34.81   |23.07 |0    |17.25 |30   |50      |100  |▅▇▆▅▃▃▁▁ |\n|quality_overall           |Overall, what do you think of the quality of the waiting time for appointments in registration offices as presented before?     |numeric   |0. Extremely poor, - 100. Extremely good                                                                                                                          |0       |362      |362 |NA    |NA       |NA  |NA  |28.68   |20.26 |0    |14.25 |24   |40      |100  |▆▇▅▃▂▁▁▁ |\n|attention_check           |In which timeframe will you get an appointment in the registration offices in Hamburg?                                          |character |1 - 2 weeks. 1–2 weeks, - 3 - 5 weeks. 3–5 weeks, - 6 - 8 weeks. 6–8 weeks                                                                                          |8       |354      |362 |0     |3        |11  |11  |NA      |NA    |NA   |NA    |NA   |NA      |NA   |NA       |\n|blame_responsible         |How much do you think local politicians are responsible for the given situation in the registration offices?                    |numeric   |0. Not at all responsible, - 100. Completely responsible                                                                                                          |26      |336      |362 |NA    |NA       |NA  |NA  |55.38   |25.17 |1    |36.75 |56   |75      |100  |▂▅▅▇▇▆▆▅ |\n|blame_fault               |How much do you think the given situation is local politician's fault?                                                          |numeric   |0. Not at all politicians' fault, - 100. Completely politicians' fault                                                                                            |26      |336      |362 |NA    |NA       |NA  |NA  |52.84   |25.24 |1    |33.75 |51   |72.25   |100  |▂▅▅▇▆▆▅▅ |\n|blame_time_management     |Time management regarding the appointments for citizens?                                                                        |numeric   |0. Deserving no blame at all, - 100. Completely deserving blame                                                                                                   |27      |335      |362 |NA    |NA       |NA  |NA  |46.88   |24.85 |0    |28    |45   |65      |100  |▃▆▇▇▆▅▃▃ |\n|blame_substantial_service |Certainty that citizens receive substantial service on time?                                                                    |numeric   |0. Deserving no blame at all, - 100. Completely deserving blame                                                                                                   |26      |336      |362 |NA    |NA       |NA  |NA  |46.82   |23.57 |0    |28.75 |48   |62.25   |100  |▂▆▆▇▇▅▂▂ |\n|blame_employees           |Amount of employees that are working in the registration offices?                                                               |numeric   |0. Deserving no blame at all, - 100. Completely deserving blame                                                                                                   |27      |335      |362 |NA    |NA       |NA  |NA  |55.79   |26.25 |0    |34    |58   |76      |100  |▂▃▆▆▇▇▅▆ |\n|blame_overall             |Overall, to what extent do you believe local politicians are deserving blame for the waiting times as displayed to you earlier? |numeric   |0. Deserving no blame at all, - 100. Completely deserving blame                                                                                                   |26      |336      |362 |NA    |NA       |NA  |NA  |49.48   |23.81 |0    |30    |50   |67      |100  |▂▆▅▇▇▆▃▂ |\n|blame_willing             |Overall, to what extent are you willing to attribute blame to local politicians for the waiting times as displayed earlier?     |numeric   |0. Not at all willing, - 100. Completely willing                                                                                                                  |32      |330      |362 |NA    |NA       |NA  |NA  |46.65   |24.51 |0    |28.25 |45   |66      |100  |▃▅▇▇▅▆▂▂ |\n|political_orientation     |In politics people sometimes talk of 'left' and 'right'. Where would you place yourself on a scale from 0 to 10?                |numeric   |0. extreme left, - 10. extreme right                                                                                                                              |34      |328      |362 |NA    |NA       |NA  |NA  |3.87    |1.61  |0    |3     |4    |5       |9    |▁▅▇▅▆▂▁▁ |\n|visit_service_center      |Did you attend a registration office in the last 12 months?                                                                     |character |No. No, - Yes. Yes, - NA. N/A                                                                                                                                       |0       |362      |362 |0     |3        |2   |3   |NA      |NA    |NA   |NA    |NA   |NA      |NA   |NA       |\n|yearbirth                 |What year were you born?                                                                                                        |numeric   |NA                                                                                                                                                              |34      |328      |362 |NA    |NA       |NA  |NA  |1990.71 |4.32  |1971 |1989  |1991 |1993.25 |1998 |▁▁▁▁▂▇▅▃ |\n|gender                    |How do you describe your gender identity?                                                                                       |character |Male. Male, - Female. Female                                                                                                                                      |34      |328      |362 |0     |3        |4   |6   |NA      |NA    |NA   |NA    |NA   |NA      |NA   |NA       |\n|group                     |Treatment group                                                                                                                 |numeric   |0. Control, - 1. Public opinion in favor of blaming, - 2. Public opinion not in favor of blaming, - 3. High intensity of pre-existing blame, - 4. No pre-existing blame |0       |362      |362 |NA    |NA       |NA  |NA  |2.05    |1.44  |0    |1     |2    |3       |4    |▇▆▁▇▁▇▁▇ |\n\n### Note\nThis dataset was automatically described using the [codebook R package](https://rubenarslan.github.io/codebook/) (version 0.8.0).",
  "creator": "Martin Sievert, Dominik Vogel, Tim Reinders, Waqar Ahmed",
  "citation": "Sievert, M., Vogel, D., Reinders, T., & Ahmed, W. (2019). The Power of Conformity in Citizens' Blame: Evidence from a Survey Experiment. Public Performance & Management Review.",
  "url": "",
  "identifier": "https://doi.org/10.7910/DVN/KYOABG",
  "datePublished": "2019-06-21",
  "temporalCoverage": "April 2017",
  "spatialCoverage": "Hamburg, Germany",
  "keywords": ["quality_time_management", "quality_service_on_time", "quality_amount_of_staff", "quality_overall", "attention_check", "blame_responsible", "blame_fault", "blame_time_management", "blame_substantial_service", "blame_employees", "blame_overall", "blame_willing", "political_orientation", "visit_service_center", "yearbirth", "gender", "group"],
  "@context": "http://schema.org/",
  "@type": "Dataset",
  "variableMeasured": [
    {
      "name": "quality_time_management",
      "description": "time management regarding the appointments for citizens?",
      "value": "0. Extremely poor,\n100. Extremely good",
      "maxValue": 100,
      "minValue": 0,
      "@type": "propertyValue"
    },
    {
      "name": "quality_service_on_time",
      "description": "certainty that citizens receive substantial service on time?",
      "value": "0. Extremely poor,\n100. Extremely good",
      "maxValue": 100,
      "minValue": 0,
      "@type": "propertyValue"
    },
    {
      "name": "quality_amount_of_staff",
      "description": "amount of staff that is working in the registration offices?",
      "value": "0. Extremely poor,\n100. Extremely good",
      "maxValue": 100,
      "minValue": 0,
      "@type": "propertyValue"
    },
    {
      "name": "quality_overall",
      "description": "Overall, what do you think of the quality of the waiting time for appointments in registration offices as presented before?",
      "value": "0. Extremely poor,\n100. Extremely good",
      "maxValue": 100,
      "minValue": 0,
      "@type": "propertyValue"
    },
    {
      "name": "attention_check",
      "description": "In which timeframe will you get an appointment in the registration offices in Hamburg?",
      "value": "1 - 2 weeks. 1–2 weeks,\n3 - 5 weeks. 3–5 weeks,\n6 - 8 weeks. 6–8 weeks",
      "maxValue": "6 - 8 weeks",
      "minValue": "1 - 2 weeks",
      "@type": "propertyValue"
    },
    {
      "name": "blame_responsible",
      "description": "How much do you think local politicians are responsible for the given situation in the registration offices?",
      "value": "0. Not at all responsible,\n100. Completely responsible",
      "maxValue": 100,
      "minValue": 0,
      "@type": "propertyValue"
    },
    {
      "name": "blame_fault",
      "description": "How much do you think the given situation is local politician's fault?",
      "value": "0. Not at all politicians' fault,\n100. Completely politicians' fault",
      "maxValue": 100,
      "minValue": 0,
      "@type": "propertyValue"
    },
    {
      "name": "blame_time_management",
      "description": "Time management regarding the appointments for citizens?",
      "value": "0. Deserving no blame at all,\n100. Completely deserving blame",
      "maxValue": 100,
      "minValue": 0,
      "@type": "propertyValue"
    },
    {
      "name": "blame_substantial_service",
      "description": "Certainty that citizens receive substantial service on time?",
      "value": "0. Deserving no blame at all,\n100. Completely deserving blame",
      "maxValue": 100,
      "minValue": 0,
      "@type": "propertyValue"
    },
    {
      "name": "blame_employees",
      "description": "Amount of employees that are working in the registration offices?",
      "value": "0. Deserving no blame at all,\n100. Completely deserving blame",
      "maxValue": 100,
      "minValue": 0,
      "@type": "propertyValue"
    },
    {
      "name": "blame_overall",
      "description": "Overall, to what extent do you believe local politicians are deserving blame for the waiting times as displayed to you earlier?",
      "value": "0. Deserving no blame at all,\n100. Completely deserving blame",
      "maxValue": 100,
      "minValue": 0,
      "@type": "propertyValue"
    },
    {
      "name": "blame_willing",
      "description": "Overall, to what extent are you willing to attribute blame to local politicians for the waiting times as displayed earlier?",
      "value": "0. Not at all willing,\n100. Completely willing",
      "maxValue": 100,
      "minValue": 0,
      "@type": "propertyValue"
    },
    {
      "name": "political_orientation",
      "description": "In politics people sometimes talk of 'left' and 'right'. Where would you place yourself on a scale from 0 to 10?",
      "value": "0. extreme left,\n10. extreme right",
      "maxValue": 10,
      "minValue": 0,
      "@type": "propertyValue"
    },
    {
      "name": "visit_service_center",
      "description": "Did you attend a registration office in the last 12 months?",
      "value": "No. No,\nYes. Yes,\nNA. N/A",
      "maxValue": "Yes",
      "minValue": "No",
      "@type": "propertyValue"
    },
    {
      "name": "yearbirth",
      "description": "What year were you born?",
      "@type": "propertyValue"
    },
    {
      "name": "gender",
      "description": "How do you describe your gender identity?",
      "value": "Male. Male,\nFemale. Female",
      "maxValue": "Male",
      "minValue": "Female",
      "@type": "propertyValue"
    },
    {
      "name": "group",
      "description": "Treatment group",
      "value": "0. Control,\n1. Public opinion in favor of blaming,\n2. Public opinion not in favor of blaming,\n3. High intensity of pre-existing blame,\n4. No pre-existing blame",
      "maxValue": 4,
      "minValue": 0,
      "@type": "propertyValue"
    }
  ]
}`