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The influence factor of voteTeam member Probl.docx

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The influence factor of vote
Team member:
Problem description
2
we evaluate the effect of age, gender, whether an individu...
https://nsd.no/european_election_database/
Random Sampling; n=188
Questions of interest
4
Is there an association between ...
Main Variables
6
Vote: binary variable. Whether an individual vote or not.
Age: age of an individual.
Female: equal to 1 f...
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The influence factor of vote
Team member:





Problem description
2

we evaluate the effect of age, gender, whether an individual actually received and listened to the entire call and whether busy or not on voting.





Dataset
3



European Election Database.
Data Source


Website
Sampling Method


https://nsd.no/european_election_database/
Random Sampling; n=188





Questions of interest
4

Is there an association between gender and whether an individual vote or not?

Is there an association between age and whether an individual vote or not?

Is there an association between whether an individual actually received and listened to the entire call and whether he/she vote or not?

Is there an association between County and individual’s county development degree and whether he/she vote or not?






Analysis to be completed
5
Qualitative variables
Bivariate variables
Correlation : vote and gender
Chi-square test: vote and gender
Regression Analysis: vote and age
Correlation





Main Variables
6


Vote: binary variable. Whether an individual vote or not.
Age: age of an individual.
Female: equal to 1 for female and 0 for male.
Contact: equal to 1 for people who actually received and listened to the entire call encouraging you to vote.
County: the development degree of the voter’s county.






Univariance analysis —— Age
7





Univariance analysis —— County
8





Univariance analysis —— Vote and Age
9

1

Correlation Analysis
2

Regression Analysis
Correlation = 0.3134

The correlation between vote and age is positive and median
The fitting equation is not significant.





Univariance analysis —— Vote and Gender
10
1

Correlation Analysis
2

Chi-square test: vote and gender
Correlation = 0.3134
The gender and vote is independent.
The correlation between vote and gender is positive and median.






Univariance analysis —— Vote and Contact
11
1

Correlation Analysis
2

Chi-square test: vote and contact
Correlation = 0.1193

The correlation between vote and gender is positive and weak






Univariance analysis —— Vote and County
12
1

Correlation Analysis
2

Regression Analysis
Correlation = -0.15787

The correlation between vote and county is negative.
Fitting equation: Vote = 0.7837 – 0.0026*County









Conclusion
13



1
There is no significant association between gender and whether an individual vote or not.
The gender and vote is not dependent and the correlation between vote and gender is positive and median

2
there an positive and weak association between whether an individual actually received and listened to the entire call and whether he/she vote or not.
The correlation between vote and county is negative, the better the county’s develop, the more voters.







THANKS



Chapter 11:
Managing Organizational Change and Crises


Introduction
In this ever-changing global economy, organizational change is inevitable
Productively managing change by drawing on the strengths of an organization keeps them healthy a.

The influence factor of vote
Team member:





Problem description
2

we evaluate the effect of age, gender, whether an individual actually received and listened to the entire call and whether busy or not on voting.





Dataset
3



European Election Database.
Data Source


Website
Sampling Method


https://nsd.no/european_election_database/
Random Sampling; n=188





Questions of interest
4

Is there an association between gender and whether an individual vote or not?

Is there an association between age and whether an individual vote or not?

Is there an association between whether an individual actually received and listened to the entire call and whether he/she vote or not?

Is there an association between County and individual’s county development degree and whether he/she vote or not?






Analysis to be completed
5
Qualitative variables
Bivariate variables
Correlation : vote and gender
Chi-square test: vote and gender
Regression Analysis: vote and age
Correlation





Main Variables
6


Vote: binary variable. Whether an individual vote or not.
Age: age of an individual.
Female: equal to 1 for female and 0 for male.
Contact: equal to 1 for people who actually received and listened to the entire call encouraging you to vote.
County: the development degree of the voter’s county.






Univariance analysis —— Age
7





Univariance analysis —— County
8





Univariance analysis —— Vote and Age
9

1

Correlation Analysis
2

Regression Analysis
Correlation = 0.3134

The correlation between vote and age is positive and median
The fitting equation is not significant.





Univariance analysis —— Vote and Gender
10
1

Correlation Analysis
2

Chi-square test: vote and gender
Correlation = 0.3134
The gender and vote is independent.
The correlation between vote and gender is positive and median.






Univariance analysis —— Vote and Contact
11
1

Correlation Analysis
2

Chi-square test: vote and contact
Correlation = 0.1193

The correlation between vote and gender is positive and weak






Univariance analysis —— Vote and County
12
1

Correlation Analysis
2

Regression Analysis
Correlation = -0.15787

The correlation between vote and county is negative.
Fitting equation: Vote = 0.7837 – 0.0026*County









Conclusion
13



1
There is no significant association between gender and whether an individual vote or not.
The gender and vote is not dependent and the correlation between vote and gender is positive and median

2
there an positive and weak association between whether an individual actually received and listened to the entire call and whether he/she vote or not.
The correlation between vote and county is negative, the better the county’s develop, the more voters.







THANKS



Chapter 11:
Managing Organizational Change and Crises


Introduction
In this ever-changing global economy, organizational change is inevitable
Productively managing change by drawing on the strengths of an organization keeps them healthy a.

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The influence factor of voteTeam member Probl.docx

  1. 1. The influence factor of vote Team member: Problem description 2 we evaluate the effect of age, gender, whether an individual actually received and listened to the entire call and whether busy or not on voting. Dataset 3 European Election Database. Data Source Website Sampling Method
  2. 2. https://nsd.no/european_election_database/ Random Sampling; n=188 Questions of interest 4 Is there an association between gender and whether an individual vote or not? Is there an association between age and whether an individual vote or not? Is there an association between whether an individual actually received and listened to the entire call and whether he/she vote or not? Is there an association between County and individual’s county development degree and whether he/she vote or not? Analysis to be completed 5 Qualitative variables Bivariate variables Correlation : vote and gender Chi-square test: vote and gender Regression Analysis: vote and age Correlation
  3. 3. Main Variables 6 Vote: binary variable. Whether an individual vote or not. Age: age of an individual. Female: equal to 1 for female and 0 for male. Contact: equal to 1 for people who actually received and listened to the entire call encouraging you to vote. County: the development degree of the voter’s county. Univariance analysis —— Age 7 Univariance analysis —— County 8 Univariance analysis —— Vote and Age
  4. 4. 9 1 Correlation Analysis 2 Regression Analysis Correlation = 0.3134 The correlation between vote and age is positive and median The fitting equation is not significant. Univariance analysis —— Vote and Gender 10 1 Correlation Analysis 2 Chi-square test: vote and gender Correlation = 0.3134 The gender and vote is independent. The correlation between vote and gender is positive and median. Univariance analysis —— Vote and Contact
  5. 5. 11 1 Correlation Analysis 2 Chi-square test: vote and contact Correlation = 0.1193 The correlation between vote and gender is positive and weak Univariance analysis —— Vote and County 12 1 Correlation Analysis 2 Regression Analysis Correlation = -0.15787 The correlation between vote and county is negative. Fitting equation: Vote = 0.7837 – 0.0026*County
  6. 6. Conclusion 13 1 There is no significant association between gender and whether an individual vote or not. The gender and vote is not dependent and the correlation between vote and gender is positive and median 2 there an positive and weak association between whether an individual actually received and listened to the entire call and whether he/she vote or not. The correlation between vote and county is negative, the better the county’s develop, the more voters. THANKS Chapter 11: Managing Organizational Change and Crises Introduction In this ever-changing global economy, organizational change is inevitable
  7. 7. Productively managing change by drawing on the strengths of an organization keeps them healthy and able to adapt to the environment Organizational Change Case Study: Merger Mayhem New Zest Manufacturing CEO Jeremy called a special meeting of management Rumors of a potential merger and branch closings made the atmosphere tense Jeremy was known for “doing more with less” so downsizing was a top concern for the managers Why people are afraid of changes? What problems may arise by downsizing? • Is there any good suggestions to ease the conflict by downsizing? Downsizing A common yet often-overlooked change in organizations, with unintended costs Employees who survive the layoffs often: Voluntarily leave the company for better options View the organization as unstable Experience enhanced workloads, leading to burnout Organizations often struggle to hire new talent and lose employees with organizational knowledge Several key steps should be followed before making the decision to downsize Critical Thinking Questions - Downsizing How does the term “survivor” help us to understand the experiences of individuals after a downsizing has occurred?
  8. 8. Identifying the Change Process Tim Brown (2009) suggests the thought process should go something like this: Begin at the beginning Take a human-centered approach Fail early; fail often Get professional help Share the inspiration Blend big and small projects Budget to the pace of innovation Laying the Foundation for Change When organizations face change, how that change is framed can have a tremendous impact on whether employees buy into the change Laying the proper foundation is vital for creating a sense of commitment to the change Employees will be more likely to be committed to the change if they are able to move beyond simple adaptation and acceptance to understanding and a sense of control Implementing Change Organizations implementing change that have the attitude that everyone is on the team and has the potential to contribute ideas will often find that employees “in the trenches” will have knowledge and insight based on observation and experience that just might improve the process Relying on the employees doing the job to offer suggestions is
  9. 9. likely to improve the process as well as create a greater sense of commitment on the part of the employee Evaluating Change Outcomes Organizations can reevaluate and change again if it isn’t working Just because an organization has changed something, perhaps even based on extensive research, doesn’t mean that the organization has to accept the results of that change Evaluation is vital Organizational Learning A successful organization is a learning organization For the organization to learn, though, there must be an attitude that recognizes the value of all team members – from the custodial staff to the CEO Just as important, there needs to be an effective system of communication The type of communication may take different forms, depending on the culture of the organization, but there must be a system in place In addition, the attitude of the organization should be one that fosters creative thinking at all levels Critical Thinking Questions – Change How might an organization’s culture influence change
  10. 10. processes? Can you think of examples of types of organizations that seem to be “learning organizations”? Crisis and Change Case Study: Takata Airbags Multiple deaths occurred as a result of problematic Takata airbags in Toyota vehicles Multiple rounds of recalls culminated in 31 million recalls in eight years, including those from other manufacturers How an organization communicates in a crisis can be a life-and- death matter What should Takata have done? What ethical concerns do you have about this crisis? Organizational Crisis “A low-probability, high-impact event that threatens the viability of the organization and is characterized by ambiguity of cause, effect, and means of resolution, as well as by a belief that decisions must be made swiftly” (Pearson & Clair, 1998, p. 60) Organizations typically either try to keep crisis from occurring in the first place, or try to soften the impact when crisis does occur Five stages of crisis include signal detection, preparation/prevention, containment/damage litigation, recovery, and learning Crisis Communication Plan Plans should be proactive, specifically: Identify a crisis team
  11. 11. Develop key messages for internal and external publics Designate a spokesperson and backup Have a system to monitor communication about the organization Have a postcrisis review plan In addition to correcting the issue, crisis communication should also reduce tension, be ethical, control information flow, and manage the recovery Crisis Communication and Image Image can be impacted positively or negatively as a result of a crisis The way a mistake is resolved, and what the organization learns in the process, is important Examples: BP Deepwater Horizon oil spill JetBlue Crisis Communication Should Be Dynamic Leaders must adapt communication to the changing environment and stakeholder concerns Leaders must continually assess the situation, environment, and changing variables is necessary Leaders must remain consistent in organizational values Context Matters For-Profit Organizations Longer processing times can create both negative and positive crisis situations for larger corporations Family Entrepreneurship Less time required to deal with change and crisis, but potential
  12. 12. for big differences for the organization Nonprofit Organizations Very specific missions create potential change challenges Government Sector Resistance to change may take a more political form Chapter 10: Managing Conflict Introduction Workplace conflicts are often not productive Take time away from one’s job Take time away from providing customer service Strained emotion often lingers Conflict can lead to innovation and creativity Conflict must be managed – not ignored Conflict Defined An expressed struggle between at least two interdependent parties, who perceive incompatible goals, scarce rewards or resources or expectations that are not being met, and interference from the other party or parties in achieving their goals Conflict vs. Difference of Opinion Interdependent parties Incompatible goals
  13. 13. Interference If we perceive something, we will often act as if it is true Managing Conflict Dimensions of Conflict History: experiences with the party or other conflicts Source: can be the other person or something less personal Perceptions: assumptions and prejudices often make us think something is true even if it is not Emotions: controlling emotions in a positive manner can lead to positive conflict resolution Behavior: good, controlled behavior can move us toward positive results Effective vs. Dysfunctional Responses Differentiation: “Parties raise the conflict issues and spend sufficient time and energy clarifying positions, pursuing the reasons behind those positions, and acknowledging their differences stage determines differences” (Stutman, 2009, p. 14) Opportunities to develop understanding during this stage Case Study: Zest Manufacturing Wars A small group of managers met for their weekly meeting, and conflict arose Two managers were at odds because both failed to ask for rationale and allowed their emotions to flare A third manager facilitated a conversation to help both parties see how to resolve the conflict Perception was key; both managers perceived that the other was questioning their ability to do their job
  14. 14. Have their been times when emotion influenced your perception of something? Did it help or hurt? Conflict Within the Organization Personality conflicts: arise out of differences in the collection of qualities that make people who they are but that also don’t meet our expectations Role confusion: lack of clarity over expectations of our position or fulfilling our job duties Intragroup conflict: conflict within a group Intergroup conflict: conflict between two or more groups Intraorganizational conflict: conflict within an organization Critical Thinking Questions - Conflict Why does conflict often escalate so quickly? In today’s modern society, what other potential sources of conflict within organization can you think of? Styles of Dealing with Conflict Avoiding Those who prefer avoidance recognize a conflict exists, but tend to want to withdraw from, ignore, or suppress it Low concern for satisfying concerns of themselves or others Can be useful when issues are trivial, there is no chance of satisfying your concerns, or disruption outweighs benefits of resolution Competing
  15. 15. Individuals who use competition place their own concerns as more important than the concerns of others “I win, you lose” approach Can work when quick action is necessary Can spur creativity and innovation Can lead to one-sidedness and harmful for building trust Accommodation The opposite of competing Putting one’s needs and concerns aside in order to focus on concerns and needs of others Useful when one is wrong about an issue, or an issue is far more important to others, maintaining cooperation as a goal Compromise Often considered the best strategy because it is in the middle of the grid Both parties get something without excessive disruption Balance of loss and gain can be useful and seen as fair Often leaves both parties feeling dissatisfied Collaboration Ideal because of a high concern for needs of all parties involved Win-win result is the goal Collaborative people help to solve problems by being creative and looking for joint gains Trust is an important component of collaborative processes Strategic Objectives We need to consider the importance of the relationship as well as our goals and desires as we decide which tactic to use Managing conflict requires the ability to recognize the tactics of
  16. 16. others and adjust our own tactics to complement and/or counter the other party in an effort to achieve the final goal Organizational Conflict and Power Power can determine: How conflict gets resolved What goals a group will pursue How a group’s resources will be distributed Many conflicts have asymmetrical power Forms of Power Formal power is based on an individual’s position in an organization: Coercive power Reward power Legitimate power Personal power is derived from one’s unique characteristics: Expert power Referent power Critical Thinking Questions - Power Consider conflicts in which you have been involved where power has been used by either yourself or the other party Was power used in a productive way? How did the parties to the conflict feel after power was used? Third Party Intervention
  17. 17. • In the following three special types of organizational conflicts, it is necessary to bring in a third party. Whistle-blowing, sexual harassment, discrimination • To deal with conflicts via third party intervention: Negotiation Mediator Arbitration (conventional interest arbitration, final offer arbitration) Judicial approach Case Study- Email Fiasco Phil is unhappy with the hiring of new manager Marshall, and the promotion of Trish Marshall suggested changing the inventory process, and Trish supported it while Phil did not Marshall sent an email to the entire company that derided both Trish and Phil What types of conflict exist in this case? What other issues contributed to this conflict situation? Conflict Outside: Dealing with an Angry Public When conflict has moved outside the organization and we are dealing with a potentially angry public, remember there are some key variables to consider in our response: What are the facts of the situation? What emotions are driving the publics’ perception? What are the contextual variables that create and sustain the crisis? What are/should be the organizational actions taken in response to the critical event(s)? Organizations must recognize the various emotions involved and seek to “step into the shoes” of others and understand their varying perspectives
  18. 18. Context Matters For-Profit Organizations Dealing with conflict takes time, which can be both positive and negative Family Entrepreneurship Conflict can be dealt with more quickly but can also infect an entire organization faster Nonprofit Organizations Presence of volunteers complicates conflict processes Government Sector Unique rules and guidelines may produce additional interorganizational conflicts Sheet6SUMMARY OUTPUT回归统计Multiple R0.157872585R Square0.0249237531Adjusted R Square0.0196530707标准误差0.47904705观测值187方差分析dfSSMS FSignificance F回归分析11.08518287521.08518287524.72875258350.03093165 97残差18542.45492407670.2294860761总计18643.5401069519Co efficientsStandard deviationt StatP-valueLower 95%Upper 95%Intercept0.78370.07859.98860.00000.62890.9385County- 0.00260.0012-2.17460.0309-0.0049-0.0002 Sheet2personsvoteagefemalecontactcounty0.313412934- 0.1578725851149118821830075ActualExpected30600060voteN ot votevoteNot vote40511065female6843111female69.301587301641.69841269 8411150420147male502878male48.698412698429.30158730167 86174111811871189118711897074119780671188Chi- Squared91680178voteNot vote101511027female0.02444575330.04062815330.0650739066
  19. 19. 11086112male0.03478818730.05781698740.0926051747121670 1840.05923394060.09844514070.1576790813<3.84Accept Null1313501431412810270.1193784224151441024161410072A ctualExpected171600118voteNot votevoteNot vote181711084contact592685contact49.470899470935.5291005 29185191581183not contact5945104not contact60.529100529143.47089947091042003611841107918911 07918921043109722142102Chi-Squared231700060voteNot vote241570078female1.83549840142.55575726774.3912556691 250751078male0.03862850110.05378652060.092415021726066 11841.87412690252.60954378834.4836706908>3.84Reject Null2718511228156111429083018730124011431162106532022 01843316210783405200813515400203602500603714900653804 71178391571071401741183410261078420200075431831197441 55109745165108446173111147175107348160002149031109750 16710785115910715202500155302111735415300785503911155 61751030570301197581601139590491060601271043611690114 62166111563183112464052109765171108466023108367052106 76815701976906410757003200217114000977214111367318711 84740420047751600075761381188771741157804011977917311 88801721165810390058203311758314710218417311148505200 78860401036871870165881360071891490078901560130910861 07892182118893029002194048013095066002496154012197161 00699816600879903410781000390097101193001810215510651 03149111110416700361051471014106179009710715001241081 71016510913501271100571187111184117811215711511318010 18114140009711515710511618411471171291073118073114711 90490197120179016912108801361221780175123036109712414 91197125136117812617100151270231015128151117112903911 67130167107313107911731321230078133072112413517711781 36133013913705110431391451097140164101814107900971421 38009714304501811440870071145080109714605110971471710 16914804401781491420111500311071151163117815215600731 53175116915416110781550271081156160112415716210841581 57111515904510751601551160161175111116206500181630291 18416415110811650211043166138008016702010971681540078
  20. 20. 16917010781701410069171197112172021004717314210871740 32106917505900111761770178177156005178042108417918511 60180145018118114110601821630178183144002118417610751 8504010601861380172187149117518815201751890440167 Sheet5personscompetivvote00treatmenpseudo_tcountyst_senst_ hsevote98newregpid_majagefemalevote02contactpseudo_cbusyb ad_countytreat_realtreat_pseudononcomppseudo_nstatecomp_mi comp_iafem_missfemale2lchcpseudo_portionpagecatagecat2211 22884895100491111001110101010.01401594845111117523102 83010000111110100100.01608182802101160241026000000011 1110100100.015671860601112265499700051100010111110101 010.0116165505011022472855102420011001110100010.01059 85424021122182753101741111001110101010.01805997470110 119711001741011001110101100.0146777747021011884895102 671011001110101100.0168242666521122782957100680111001 110100010.0169955686511122274895001511100001111101010 10.011616550501102224896000861011001110101010.0165775 8685211118424102670111001110100100.016824266651111143 2856101350111001110100100.009868334351112227489510128 110000111110101010.0091878282511111242855100441100001 11110101100.01081694440211117235102410100001111101001 00.0129212404021122182753102600111001110100010.015671 8606011111842300271110000111110101100.014237270702111 1832957101581111001110101100.015357585521022842410036 1011001110101010.012280336351112297285500143100000111 110101010.0107072424011011248960124211000011111010110 0.0085832424021122602410170010000111110100010.0173433 707011122785010000057010000111110100010.0123482565521 11178509900175100000111110101100.01824367475211118424 102661011001110101100.0166546666511122248960018511110 01110101010.01641048485210111426510115611110011101011 00.0121975565521111874896102830011001110100100.019780 2828021122142651101240111001110100010.010867524182111 165499810262110000111110101100.0159929626021022842400 2220011001110100010.010648122182112278499810162110000 111110101010.0159929626021122812652101520000001111101
  21. 21. 00010.014449652501112220489510254010000111110100010.0 119769545021011602410025000000111110100100.0109788242 51111165499710249010000111110100100.01138234845111227 850100001471011001110101010.0111527464521111713500057 110000111110101100.0152025655111228329570007411110011 10101010.01467777470211227850100000261000001111101010 10.011091226252101175275301220000000111110100100.0084 491201811122972855102831111001110101010.0160818280111 11971110155110000111110101100.01209945455111228424100 65110000111110101010.01339516465211111126521027311110 01110101100.01787817270211117349970027511000011111010 1100.0182436747521111213600160010000111110100100.0156 71860601101197275400031100000111110101100.00947363030 2112278499810267110000111110101010.016824266652111171 3510259110000111110101100.015513658551101115295701025 000000111110100100.0072139242511111734997002211011001 110101100.0085539201811111785099102530100001111101001 00.0118555525011022152958000391011001110101010.010279 2383511111303610175110000111110101100.014827474751101 19711001301011001110101100.00937743030211223929580006 01111001110101010.01567186060211226024002491000001111 10101010.01401594845211224328560022711000011111010101 0.0112048262511122142651102690111001110100010.0139509 686511022152957001661111001110101010.0135319666521122 242651100831111001110101010.0197802828011022972753101 52100000111110101010.01173545250211118424102711100001 11110101100.01751987070110228329570002310000011111010 1010.008730522181101167285601052100000111110101100.00 9506525021111972754100570111001110100100.015202565511 0227527530116400000111110110010.010743864601101121360 0232000000111110100100.009570732302111197285510140010 000111110100100.0127904404021122364997102411111001110 101010.01292124040111118424102871111001110101100.0167 46486851102247285500042000000111110100010.01059854240 11111752310260010000111110100100.01273160602111188489 5102381111001110101100.012532838352111152958101741111
  22. 22. 001110101100.0180599747011011972754001401011001110101 100.0103846404011111884895102731111001110101100.01452 94727011122654998101721111001110101010.01438267270211 115295800239000010111110100100.0126613835210117527530 01331011001110101100.01191093230111222135101471100001 11110101010.01115274645211221426511017311110011101010 10.0178781727011011785010001152000000111110100100.009 50652501101136499700240100000111110101100.01038464040 21122654997102870111001110100010.02059548685211117135 10236010000111110100100.01228033635111117850100000490 10000111110100100.01138234845211223036101560111001110 100010.015048556551112278509910286100000111110101010. 0165775868511122884895102821111001110101010.015918882 8011011213600029000000111110100100.009282128252102230 36102480011001110100010.01387424845111112428551016600 0000111110100100.013531966652112221350015401110011101 00010.014746154501112269489610261010000111110100010.0 12861260602111187489610166010000111110100100.01665466 6651101178285600034100000111110101100.009768134302102 297275400239000000111110100010.0126613835110111827531 0193010000111110100100.017795492902112265499810255110 000111110101010.0148965545511122112652101491111001110 101010.011382348451101136499700067010000111110100100. 013670266652111114265110247110000111110101100.0137344 64521122971210179010000111110100010.01899667875211222 42855102500111001110100010.01415950502112265499700271 0111001110100010.017519870702112227489500135011100111 0100010.0121559343511011874896000571011001110101100.0 1234825655111227850100102841111001110101010.016244984 802111152958102571111001110101100.0152025655210111827 5301180110000111110101100.015566480801111197110004001 0000111110100100.010384640402112252958101571100001111 10101010.015202565511111472855101841111001110101100.0 16244984802111173499700029110000111110101100.01143552 82521111472855101731011001110101100.01787817270110229 712100490011001110100010.0113823484521111694896112790
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